To eliminate this intelligence gap, enterprise collaboration leader Atlassian announced the launch of Code Context, a major extension of the Atlassian Teamwork Graph.

By making the connection between codebase comprehension of a large size with multiple repositories and organizational knowledge from Jira, Confluence, Loom, as well as 50+ integrations, Atlassian creates a secure context layer for reasoning about code as well as business intent by humans as well as AI agents. The launch represents an important milestone for the Software Development, DevOps, and Enterprise AI Orchestration industry, since now it is time to move beyond code generation and toward unified, graph-based context.

Technical Performance: Deep Codebase Understanding Meets Organizational Memory

The primary technical breakthrough behind Code Context is its queryable, permission-aware representation of connected codebases. Developers and third-party AI agents can use exact search, natural-language queries, and semantic retrieval to find relevant source code across hundreds of repositories simultaneously.

Also Read: Quantinuum and Oracle Partner to Bring Hybrid Quantum Computing to Oracle Cloud Infrastructure 

Key capabilities of the new platform integration include:

Teamwork Graph CLI Interoperability: Allows third-party coding agents like Claude Code, Cursor, and Codex to query multi-repo codebases, architectural specs, and Jira issues natively through a command-line interface before planning or writing code.

44% Accuracy Boost with 48% Fewer Tokens: In internal benchmarks, AI agents enriched by the Teamwork Graph delivered 44% more accurate results while consuming 48% fewer tokens compared to agents operating without graph context.

Unified Architectural Memory: Combines source code with related Jira work items, Loom video transcripts, and Confluence decisions, providing agents with the full “why” behind software architectures.

As Mark Walz, Chief Technology Officer at SpotOn, noted: “When an agent starts in the wrong place, everything slows down and costs more. Developers end up explaining where to look, why the code works the way it does, and what else it touches. Code Context puts all of that in front of the agent from the start, so it can focus on getting the work done.”

Transforming the Software Development and Enterprise AI Industry

Atlassian’s integration of deep codebase indexing into its core Teamwork Graph triggers structural shifts across the software engineering software landscape.

The Shift from “Code Completion” to “Contextual Reasoning”
First-generation AI coding tools competed primarily on autocomplete speed and single-file suggestion quality. However, enterprise software development rarely happens in isolation.

Code Context exposes the limits of isolated AI tools. As engineering teams deploy autonomous agents across complex multi-service architectures, developer tools are being re-evaluated on contextual depth. Vendors that cannot ground AI models in enterprise-wide institutional memory will struggle to deliver reliable output on complex projects.

Standardizing the Open “Context Graph” Layer
Historically, software vendors attempted to lock developers into proprietary development environments.

By exposing Code Context via the open Teamwork Graph CLI, Atlassian turns its graph infrastructure into a universal context provider for any IDE, terminal, or third-party agent. This positioning cements the context engine rather than individual coding tools as the primary control plane for enterprise AI engineering.

Broad Operational Impact on Enterprise Businesses

For enterprise organizations looking to accelerate software delivery while controlling AI cloud spending, adopting graph-grounded codebase intelligence provides clear operational and financial advantages:

Insulating IT Budgets Against Escalating AI Token Expenses
Unfocused LLM queries that scan massive code repositories consume millions of input tokens, driving up monthly enterprise AI bills. By filtering queries through an indexed semantic graph, Code Context delivers precise snippets to agents, cutting token overhead in half while improving output quality.

Eliminating Architectural Drift to Speed Up Delivery
AI agents not having insight into the architectural rules of the system as a whole tend to submit pull requests that are breaking downstream services or that go against corporate coding standards. Giving the agents permission-aware and enterprise-wide context ensures that the code generated by them follows existing design patterns.

The post Atlassian Launches Code Context to Bridge Codebase Intelligence with Enterprise Knowledge appeared first on ITDigest.

Also Read: Spotfire Launches Push Compute on Snowflake AI Data Cloud to Accelerate Industrial Analytics 

Highlighting the critical operational impact of the new offering, “Data integrity and process governance are non-negotiable for organizations running mission-critical SAP environments, especially as they modernize to the cloud,” said John, Vice President of Product Management at Precisely. “With Automate Evolve Cloud Essentials, we are empowering business teams to automate complex data workflows with confidence, ensuring that data is accurate, compliant, and actionable from the moment it enters the system.” Ultimately, this latest release reinforces Precisely’s commitment to delivering enterprise-grade data integrity solutions, allowing organizations to maximize the ROI of their SAP investments while establishing a foundation of trusted data across all digital transformation initiatives.

Read More: Precisely Closes the SAP Automation Governance Gap with Automate Evolve Cloud Essentials

The post Precisely Introduces Automate Evolve Cloud Essentials to Bridge SAP Governance Gaps appeared first on ITDigest.

Also Read: Kyndryl to Acquire Healthcare IT Leaders to Accelerate AI-Driven Health Transformation

Highlighting the platform’s focus on seamless patient access, “Patients today expect the same level of convenience, personalization, and immediacy from their healthcare providers that they experience in every other digital aspect of their lives,” said Seema Verma, Executive Vice President and General Manager, Oracle Health and Life Sciences. “With our AI-powered patient portal, we are providing health systems with a modern, connected platform that empowers patients to take control of their health journeys while allowing care teams to spend less time on routine administrative tasks and more time delivering high-quality, personalized care.” In conclusion, the commercial launch provides the healthcare system with a scalable base to enhance efficiency and raise the standards of healthcare delivery while satisfying the changing patient demands in the new digital healthcare environment.

Read More: Oracle Health’s AI-Powered Patient Portal Now Generally Available

The post Oracle Health Launches AI-Powered Patient Portal to Elevate Engagement appeared first on ITDigest.

With this release, Intuit continues their move to support the various stages of the financial operations of a business from mid-market. QuickBooks Online Advanced gives high-growth companies a unified, sector-specific financial operating system while Intuit Enterprise Suite, Intuit’s AI-natively built Enterprise Resource Planning (ERP) platform is expanding upwards with new advanced features that enable multi-entity consolidation, multi-currency accounting and deep industry-specific workflows.

“Finance teams need AI they can stand behind when asked how a number was reached,” said Ashley Still, EVP and GM, Small Business and Mid-Market, Intuit. “That’s true whether you’re a high-performing business on QuickBooks Online Advanced or a complex, multi-entity organization on Intuit Enterprise Suite. Our latest innovations give finance leaders the industry-specific depth and instant insights they’ve been asking for, built into the way they already work.”

Also Read: Mercury Unveils Mercury Spend with AI Agent Cards and Intelligent Budgets 

Expanding Conversational AI Across Financial Operations

The integration of Intuit Intelligence Chat arrives as finance executives increasingly embed artificial intelligence into daily operations. According to Intuit’s 2026 Future of Finance Report, high-growth mid-market finance teams are more than twice as likely to leverage AI automation compared to slower-growth peers.

Operating as an intelligent conversational layer, Intuit Intelligence Chat allows Chief Financial Officers and controllers to query real-time performance, detect transactional anomalies, generate custom reports, and execute routine workflows using plain-language prompts without leaving the platform. The assistant acts only upon explicit user confirmation, maintaining strict governance, auditability, and human oversight.

Accounting firms are leveraging these agentic capabilities to accelerate client book closing and advisory services.

QuickBooks Online Advanced: Consolidated Financial Management for Growth Teams

QuickBooks Online Advanced has unified core financial operations into a single subscription tier, embedding accounts payable automation, merchant payments, business intelligence, and AI-driven bookkeeping directly into the core tech stack.

Books Upkeep Automation: A continuous AI service that reconciles routine transactions under user-defined rules, surfacing only high-friction exceptions for human review.

Bill Pay Elite: Includes a complete accounts payable hub with unlimited free ACH transactions and 1099 e-filing capabilities at no extra subscription charge.

Built-in Business Intelligence: Features redesigned KPI scorecards and real-time class filtering that automatically update executive dashboards, management reports, and scenario forecasting models.

Specialized Workflows for Construction, Manufacturing, and Nonprofits

To accommodate complex operational realities, Intuit introduced dedicated functionality across key verticals:

Construction: Delivers real-time project profitability tracking and AI estimation tools in QuickBooks Online Advanced. In Intuit Enterprise Suite, project list upgrades support hundreds of active jobs, custom dimensional reporting filters, and role-based data permissions for project managers.

Manufacturing & Inventory (Beta): Adds multi-level bills of materials (BOM) and multi-unit-of-measure tracking in Intuit Enterprise Suite, eliminating manual conversion errors in cost of goods sold (COGS) calculations.

Nonprofits (Beta): Introduces Balance Sheet by Dimension in Intuit Enterprise Suite, allowing finance teams to monitor assets, liabilities, and net assets across individual grants, restricted funds, and programs.

Enterprise-Grade Infrastructure and Multi-Currency Scale

To support international expansion and multi-entity operations, Intuit Enterprise Suite expanded its structural framework with 95% of migrating clients going live in 30 days or less:

Multi-Currency Processing (Beta): Utilizes a centralized, permissioned exchange rate table, automatically calculating realized and unrealized gains and losses in full compliance with ASC 830 and IAS 21 standards.

Header-Level Dimensions: Enables dimensional tagging across billable expenses, time tracking, and recurring payments with multi-level pivot views.

Data Migration Engine: Ensures smooth data transfers from QuickBooks Desktop, preserving historical inventory costing models, unit metrics, and report templates with automated pre-live validation.

“Because we can switch between companies and run consolidated reports, it allows us to standardize and make things uniform,” said Jason Corby, founder and CFO, HFMM Legacy Group. “I’ve saved 10 to 15 hours a week.”

The post Intuit Expands Mid-Market Platform with Conversational AI and Deep Industry Workflows appeared first on ITDigest.

As patients’ out-of-pocket costs of healthcare increase, it becomes more difficult for care providers to collect balances directly from patients through inefficient, paper-based billing processes. WellSky Pay brings the next level of innovation to the revenue cycle management lifecycle, allowing organizations to automate the entire process of point-of-care transaction processing, payment plan management, centralized reporting, and automated reconciliation.

Digitalizing the Revenue Cycle Management Process for Healthcare Providers

WellSky Pay offers full transparency in the process of revenue cycle management by getting rid of paper invoices and manual accounting ledger updating.

Also Read: Inovalon and OMNY Health Partner to Launch Linked Real-World Dataset to Accelerate Research and Improve Patient Outcomes

Key functional advantages of the WellSky Pay solution include:

Automated Workflow Reconciliation: Synchronizes patient transaction data directly into core WellSky care management systems, eliminating manual data entry errors.

Flexible Patient Financing: Allows healthcare facilities to establish customized, automated payment schedules to improve collection rates on large balances.

Point-of-Care & Digital Payments: Enables immediate payment processing during clinical encounters, online interactions, or through self-service patient portals.

Comprehensive Financial Analytics: Consolidates transaction tracking through intuitive dashboards to give revenue cycle managers real-time insights into cash flow and outstanding accounts receivable.

“Healthcare organizations need payment experiences that are easier for patients and more efficient for staff,” said Bill Miller, chairman and CEO of WellSky. “With the WellSky Pay solution, we’re giving our clients a practical way to digitize patient payments, reduce administrative burden, and simplify the path from payment collection to reconciliation within the systems their teams already use.”

Driving Measurable Financial Performance and Accelerated Cash Flow

Early deployment benchmarks demonstrate substantial financial and operational improvements for healthcare organizations transitioning to the digital-first payment model:

Superior Repayment Benchmarks: Achieves a 65% repayment rate, significantly outperforming the 45% healthcare industry standard.

Accelerated Accounts Receivable (A/R): Reduces average A/R collection cycles by 9.4 days.

Immediate Revenue Lift: Delivers a 23% surge in total patient collections within the initial 90 days of platform adoption.

By unifying patient-facing payment experiences with backend administrative workflows, WellSky Pay enables healthcare organizations to lower operating costs, minimize collection friction, and maintain healthy capital reserves.

The post WellSky Launches WellSky Pay to Streamline Patient Billing and Reconciliation appeared first on ITDigest.

This ranking focuses on security-first static application security testing. It does not assume SonarQube must be removed from every code-quality workflow. Many enterprises keep SonarQube for maintainability metrics while adopting a dedicated AppSec platform for SAST. Others prefer to consolidate quality and security in one product. The right choice depends on whether the target is a specialist SAST engine or a broader application security platform.

Aikido Security ranks first because it combines modern SAST with AI-assisted code review, broad AppSec coverage, enterprise controls and a direct route from finding to fix. Semgrep is an excellent focused alternative for customizable, fast code security, while Checkmarx, Veracode, Black Duck and Fortify offer mature enterprise SAST depth for complex programs.

Quick comparison

How we ranked the tools

The order reflects practical fit for the stated enterprise use case. It is not a claim that one product is universally better for every architecture.

• Security-specific detection depth, including inter-file data flow, taint analysis, framework awareness and support for common vulnerability classes.
• Signal quality, triage context, suppression governance and the clarity of remediation guidance.
• Feedback speed and integration across IDEs, pull requests, CI/CD and issue trackers.
• Enterprise controls such as SSO, role-based access, policy gates, auditability, compliance reporting and local or self-managed analysis.
• Platform breadth beyond SAST where it improves prioritization or reduces tool sprawl, without treating breadth as a substitute for code-analysis quality.

The best tools, ranked

1. Aikido Security – Best overall SonarQube alternative for enterprise SAST

Official product page: www.aikido.dev/code/static-code-analysis-sast

Aikido Security is the best overall SonarQube alternative for enterprises that want security-first static analysis within a broader application security platform. Its SAST capability analyzes source code across major languages and development platforms, supports custom rules and fits into IDE, pull-request and CI/CD workflows. Aikido also adds AI Code Quality and AI Code Analysis for logic, authorization and business-context issues that deterministic SAST may not capture alone.

The platform’s enterprise value extends beyond the engine. Security teams can govern policies, release gates, access, audit history and compliance reporting across a portfolio, while local scanning options support strict source-code and data-residency requirements. Native SCA, secrets, IaC, container, DAST, API and cloud security add context and reduce the need to operate SonarQube beside a separate scanner for every AppSec category.

Why it stands out

• Security-focused SAST combined with AI code review and broader native AppSec coverage.
• Enterprise SSO, user administration, RBAC, policy gates, audit and compliance controls.
• Local scanning and support for GitHub, GitLab, Bitbucket and Azure DevOps estates.
• Developer remediation through PRs, CI/CD, IDEs and integrated issue workflows.

Best for: Enterprises that want to move from code-quality-led security to a unified, governed application security platform.

Considerations: Teams that rely on highly specialized SonarQube quality profiles or exhaustive technical-debt metrics should map those quality requirements separately. Validate priority languages, custom rules and the largest repositories in a proof of concept.

2. Semgrep – Best for fast, customizable developer-first SAST

Official product page: semgrep.dev/products/semgrep-code

Semgrep is one of the strongest focused SonarQube alternatives for modern enterprise SAST. It combines fast static analysis with an accessible rule syntax, data-flow analysis, centralized policy and pull-request feedback. Security engineering teams can build and distribute organization-specific checks without the operational model of a traditional heavyweight SAST platform.

The commercial AppSec platform adds software supply chain and secrets coverage, AI-assisted triage and enterprise administration around Semgrep Code. Semgrep is especially compelling when custom guardrails, developer speed and security-team extensibility are more important than broad code-quality dashboards or native DAST and cloud security.

Why it stands out

• Fast scans and strong developer workflow.
• Readable, extensible rules for custom security policies.
• Modern data-flow analysis with centralized AppSec management.

Best for: Enterprises that want a programmable, high-speed SAST platform operated closely by security engineering.

Considerations: Broader code quality, DAST, API, container and cloud posture requirements may need additional products. Custom rule programs require governance, testing and maintenance.

3. Checkmarx One – Best for complex, policy-heavy enterprise SAST

Official product page: checkmarx.com/product/application-security-platform/

Checkmarx One is a mature security-first alternative for enterprises that need deep SAST, broad language coverage and centralized policy across a large application estate. The platform also includes SCA, secrets, IaC, API and posture capabilities, allowing security teams to build a formal multi-discipline AppSec program around the static-analysis engine.

Checkmarx is particularly relevant for regulated organizations, legacy codebases and portfolios that require extensive customization. Its depth and flexibility can come with more implementation and tuning effort than developer-first tools. Buyers moving from SonarQube should test both security yield and the impact on build and developer workflows.

Why it stands out

• Mature enterprise SAST and broad technology support.
• Centralized policy, reporting and application governance.
• Strong fit for regulated and heterogeneous portfolios.

Best for: Large enterprises with dedicated AppSec teams, complex policies and legacy as well as modern code.

Considerations: Plan for ruleset tuning, implementation and developer enablement. The platform may be more capability than teams need when the requirement is a focused, easily operated SAST replacement.

4. Veracode – Best for centralized SaaS SAST and assurance

Official product page: www.veracode.com/products/binary-static-analysis-sast/

Veracode is a long-standing enterprise SAST alternative with a SaaS operating model, centralized policy and mature reporting. It is a strong fit for organizations that want consistent application assurance across business units without maintaining a large self-managed scanner infrastructure.

Veracode also offers dynamic and software composition analysis, making it suitable for broader enterprise testing programs. The platform should be tested for feedback speed, build requirements and developer usability on the organization’s real technology stack. Its strengths are formal governance and assurance rather than serving as a direct replacement for every SonarQube code-quality metric.

Why it stands out

• Mature SaaS static analysis and policy management.
• Strong portfolio reporting and regulated-program fit.
• Broader AST portfolio beyond SAST.

Best for: Enterprises prioritizing centralized assurance, auditability and a mature SaaS delivery model.

Considerations: Validate developer feedback loops, language and build support, and the need for adjacent code-quality tooling. Cloud, IaC and container coverage may involve separate capabilities.

5. Black Duck Polaris – Best for Coverity-based SAST plus enterprise SCA

Official product page: www.blackduck.com/platform.html

Black Duck Polaris combines Coverity static analysis with Black Duck software composition analysis and additional security capabilities in a cloud platform. It is a credible SonarQube alternative for enterprises that want mature SAST and SCA from one established vendor, especially when open-source risk and license management are major requirements.

Polaris can support centralized administration and developer workflows at scale. Existing Coverity or Black Duck customers may find it a natural consolidation path. New buyers should examine product packaging, scan architecture and how posture, DAST and remediation requirements are handled across the wider Black Duck portfolio.

Why it stands out

• Established Coverity SAST and Black Duck SCA engines.
• Enterprise-scale SaaS administration.
• Strong fit for combined code and open-source risk programs.

Best for: Enterprises that want mature static analysis and SCA under a common vendor platform.

Considerations: Clarify entitlements and boundaries between Polaris, Software Risk Manager and individual scanners. Evaluate PR feedback and workflow simplicity against newer platforms.

6. OpenText Fortify – Best for legacy languages and flexible deployment

Official product page: www.opentext.com/products/static-application-security-testing

OpenText Fortify SAST is a strong SonarQube alternative for enterprises with demanding language coverage, extensive legacy code or deployment constraints. It supports cloud and self-managed operating models and is backed by a mature security research and rules ecosystem.

Fortify is most effective in a formal AppSec program with analysts and administrators who can tune rules, manage findings and integrate results into delivery. It offers depth and flexibility, but organizations moving away from SonarQube because of operating burden should compare the full administrative workload and developer experience.

Why it stands out

• Deep enterprise static analysis and broad language coverage.
• Flexible SaaS and on-premises deployment.
• Strong compliance and customization capabilities.

Best for: Regulated enterprises, legacy-heavy portfolios and organizations requiring self-managed SAST.

Considerations: Expect meaningful implementation and tuning. Test incremental scan performance, issue clarity and integration into pull requests and developer tools.

7. Snyk Code – Best for developer-centric cloud-native SAST

Official product page: snyk.io/product/snyk-code/

Snyk Code is a developer-oriented SAST alternative that emphasizes fast analysis, inline explanations and remediation in IDEs and pull requests. It integrates naturally with Snyk’s open-source, container and IaC products, making it attractive to cloud-native enterprises already using the broader platform.

Compared with SonarQube, Snyk Code is more security-centered and less focused on comprehensive maintainability metrics. Enterprise buyers should evaluate the full Snyk package, role and policy model, reporting and total licensing across a large developer population.

Why it stands out

• Fast feedback in IDE and pull-request workflows.
• Strong connection to Snyk’s SCA, container and IaC ecosystem.
• Developer-friendly explanations and remediation guidance.

Best for: Cloud-native enterprises that want developers to own static-analysis remediation within a broader Snyk program.

Considerations: Model total platform licensing and confirm requirements for custom rules, local analysis, legacy languages and non-SAST testing. A separate quality platform may still be useful.

8. GitHub Code Security – Best for GitHub-native enterprise SAST

Official product page: github.com/security/advanced-security

GitHub Code Security provides CodeQL-based code scanning, dependency security workflows and campaign-oriented remediation inside GitHub. It is a logical SonarQube alternative for organizations that have standardized on GitHub Enterprise and want SAST results managed directly in repositories and pull requests.

Native workflow and central GitHub administration are its main advantages. The trade-off is ecosystem dependence: non-GitHub repositories and broader AppSec layers require other tools. Enterprises should also distinguish code-security coverage from the separate secret-protection entitlement and model per-committer pricing at scale.

Why it stands out

• Deep integration with GitHub repositories and developer workflows.
• CodeQL query ecosystem and security campaigns.
• Straightforward administration for GitHub-standardized estates.

Best for: Enterprises operating predominantly on GitHub and prioritizing native code scanning.

Considerations: It is not source-control neutral and does not replace broad DAST, API, cloud or multi-SCM security. Evaluate licensing and CodeQL coverage for the languages in scope.

How to choose the right platform

Define security depth requirements

List the vulnerability classes, frameworks, languages and inter-file data flows the program must detect. Use known internal examples and seeded tests rather than relying on generic benchmark claims.

Compare signal and explanation

Review true positives, false positives, trace clarity, severity rationale, suppressions and fix guidance. The best SAST program is the one developers can understand and act on consistently.

Test the feedback loop

Measure time from commit to result, build impact, PR annotation, IDE support and the number of steps required to create or apply a fix. Slow feedback turns SAST into a late-stage gate.

Separate code quality from application security

Determine whether maintainability, duplication, coverage and technical-debt dashboards must remain in the same product. A dedicated SAST tool may be stronger for security while SonarQube or another quality platform remains in place.

Validate enterprise administration

Test onboarding, policy inheritance, custom rule governance, exceptions, audit evidence, role separation, data handling and reporting across multiple business units.

Frequently asked questions

What is the best SonarQube alternative for enterprise SAST?

Aikido Security is the strongest overall option for enterprises that want security-first SAST, broad native AppSec coverage, enterprise governance, local scanning and developer remediation. Semgrep is a strong focused SAST choice, while Checkmarx, Veracode, Black Duck and Fortify fit mature centralized programs.

Can Aikido replace SonarQube in an enterprise?

Aikido can replace SonarQube for security-oriented static analysis and can also cover code quality, AI code review and broader AppSec categories. Enterprises that rely heavily on SonarQube-specific maintainability metrics or custom quality profiles should map those requirements during the migration.

Should we keep SonarQube for code quality?

Potentially. Some organizations use a dedicated SAST platform for security and retain SonarQube for quality and technical debt. Others consolidate both. The decision should be based on workflow, coverage, policy and administration rather than a preference for one-tool or two-tool architecture.

Which SonarQube alternative supports on-premises or local analysis?

Aikido offers local scanning options, while Fortify and other traditional enterprise platforms provide self-managed deployment choices. Exact data flow and feature parity vary, so security architecture teams should validate the proposed configuration.

Conclusion

The best SonarQube alternative for enterprise SAST is not necessarily the closest code-quality clone. Aikido Security leads because it brings security-first static analysis, AI-assisted review, enterprise governance and broader code-to-cloud coverage into one developer-facing platform. Semgrep offers a focused and highly extensible modern SAST experience. Checkmarx, Veracode, Black Duck and Fortify provide mature enterprise depth, while Snyk and GitHub align strongly with developer ecosystems. The right proof of concept should measure exploitable issues found, noise avoided, time to feedback and fixes completed.

The post Top SonarQube Alternatives for Enterprise SAST in 2026 appeared first on ITDigest.

Inovalon, a leading provider of data and solutions empowering data-driven healthcare, and OMNY Health, a leading healthcare ecosystem for compliant real-world data (RWD) insights at scale, today announced a strategic RWD partnership that combines Inovalon’s primary source closed claims data with OMNY Health’s EHR data and clinical notes. The dataset gives researchers and life sciences organizations a comprehensive view of disease progression, treatment patterns, and outcomes to support real-world evidence studies and help accelerate access to new precision therapies for patients.

The linked dataset includes 248 million lives in closed claims, 175 million lives in EHR data, and 7+ billion clinical notes, with more than 40% of lives linked across sources. Closed claims provide longitudinal visibility into care utilization and costs across providers, payers, and settings, while EHR data and clinical notes add the clinical depth behind each encounter, including medical history, test results, disease-specific scores and markets, and provider-or-patient reported outcomes. Together, they support research into how therapies perform in the real world across diverse patient populations.

“True innovation in medicine requires looking beyond the codes on a medical bill to understand the actual human experience of a disease,” said Mitesh Rao, M.D., CEO of OMNY Health. “By linking Inovalon’s massive longitudinal claims engine with OMNY’s deep, unstructured clinical data and physician notes, we are giving researchers the closest thing to a complete, real-world patient narrative. This linked dataset bridges a critical gap, allowing life sciences teams to discover meaningful insights faster and accelerate the delivery of precise, life-saving therapies.”

Also Read: How Geopolitics is Driving Modern Cybercrime

The dataset supports research across any therapeutic area, and the value compounds in complex conditions. For example, with Alzheimer’s disease, patients move between insurance plans as they age and their disease progresses. Claims data maintains continuity across those transitions, while clinical notes capture cognitive decline or improvement, so researchers gain a continuous view of both the care pathway and the underlying disease.

“HEOR teams are under growing pressure to generate evidence that is clinically rich, economically defensible, and compliant,” said Ed Chidsey, President of Inovalon’s RWD & Insights and Payer Business Units. “Inovalon and OMNY are giving researchers a complete de-identified view of the patient along with the clinical and economic insights to drive the next generation of breakthrough research.”

Inovalon and OMNY Health share a commitment to protecting patients and their sensitive health data. Privacy, security, and data quality are foundational to the offering, with de-identification under the HIPAA Expert Determination standard and continuous quality controls applied at every stage of the data lifecycle.

As part of the collaboration, Inovalon has made an undisclosed strategic investment in OMNY Health.

The post Inovalon and OMNY Health Partner to Launch Linked Real-World Dataset to Accelerate Research and Improve Patient Outcomes appeared first on ITDigest.

Traditionally, all user devices (smartphones) connected to a single cell (base station) were subjected to the same network configurations. This approach often led to service quality degradation, such as connection drops in areas with weak signals. With the growing demand for high-quality video, online gaming, and video conferencing, users increasingly require stable, uninterrupted connectivity at all times.

This newly developed AI-RAN optimization technology operates at the individual-user level rather than applying the same configuration across all users connected to a single cell. It automatically applies configurations tailored to real-time wireless conditions and the services being used. The AI learns each user’s movement patterns and service usage behavior, predicting potential service quality degradation before it occurs.

In a validation conducted in Japan in January 2026, using simulations based on data collected from DOCOMO’s commercial network and a local 5G trial field, the companies reduced the frequency of communication-speed degradation from 13.1% to 7.2%—an improvement of 5.9 percentage points—compared with operation without the technology.

Also Read: Chroma integrates MXO oscilloscopes into ATS 8000 platform, rounding out its high-end power testing ecosystem

Using aggregated data from user devices (MDT), the system analyzes individual user contexts and movement trends to detect early signs of throughput degradation before service quality declines. For instance, if a user is predicted to experience a reduction in transmission speed below the required threshold, leading to service disruptions such as buffering or reduced video quality, the system will automatically switch to the optimal configuration, e.g. frequency band, to meet service demands.

Instead of focusing on radio link failure prediction, the two companies adopted a customer-experience-driven approach aimed at supporting services such as uninterrupted video streaming. The validation demonstrated AI’s potential to enable the network to proactively predict and mitigate service-quality degradation.

Additionally, DOCOMO and Samsung developed an efficient data collection process to minimize network burden during wireless network optimization. Unlike traditional methods that required bulk collection and processing of wireless environment data, the new procedure selectively gathers only necessary information based on specific user issues, reducing strain on the network while obtaining the critical data needed for AI-driven throughput degradation prediction and network optimization. In February, the companies contributed jointly to 3GPP discussions on data collection methods, further advancing 6G technology standardization efforts.

Moving forward, DOCOMO and Samsung will continue to advance this technology and explore future 6G use cases. The two companies also intend to contribute the AI-based throughput degradation prediction technology and efficient data collection technologies developed through this work to 3GPP discussions, taking a world-leading role in realizing of AI-Centric Networks in which networks autonomously learn, predict, and optimize their behavior through AI.

“This achievement represents a significant step toward realizing more adaptive and user-centric communication experiences in future networks. Through partnerships with Samsung, DOCOMO will continue to advance AI-based technologies and explore practical applications to further enhance service quality and deliver new value to our customers,” said Masafumi Masuda, Senior Vice President and General Manager of the 6G-Tech Department, R&D Innovation Division, NTT DOCOMO.

“By shifting our research focus from overall cell performance to AI-driven individual user considerations, we have demonstrated the potential for enhanced perceived quality at the user level,” said JinGuk Jeong, Executive Vice President and Head of the Advanced Communications Research Center, Samsung Research at Samsung Electronics. “Through close collaboration with DOCOMO, we will continue securing core technologies for future communications centered around users.”

(1) Minimization of Drive Test is an automated process that anonymously collects communication quality information from user devices, such as smartphones, and applies insights to improve area coverage quality.
(2)The data transmission speed in communication, measured as the amount of data transferred per unit time, closely reflecting the actual communication speed experienced by users.

About NTT DOCOMO

NTT DOCOMO, Japan’s leading mobile operator with over 93 million subscribers, is one of the global leaders in 3G, 4G and 5G mobile network technologies. Under the slogan “Bridging Worlds for Wonder & Happiness,” DOCOMO is actively collaborating with global partners to expand its business scope from mobile services to comprehensive solutions, aiming to deliver unsurpassed value and drive innovation in technology and communications, ultimately to support positive change and advancement in global society.

About Samsung Electronics Co., Ltd.

Samsung inspires the world and shapes the future with transformative ideas and technologies. The company is redefining the worlds of TVs, digital signage, smartphones, wearables, tablets, home appliances and network systems, as well as memory, system LSI and foundry. Samsung is also advancing medical imaging technologies, HVAC solutions and robotics, while creating innovative automotive and audio products through Harman. With its SmartThings ecosystem, open collaboration with partners, and integration of AI across its portfolio, Samsung delivers a seamless and intelligent connected experience. For the latest news, please visit the Samsung Newsroom at news.samsung.com

The post DOCOMO & Samsung Electronics Achieves Successful Validation of User-level AI-RAN Technology appeared first on ITDigest.

To bridge this computational gap and make quantum-accelerated problem solving directly accessible to global enterprise organizations, quantum computing pioneer Quantinuum announced a multi-year strategic partnership with Oracle.

Under the agreement, Quantinuum’s flagship quantum computer, Helios, will be deployed directly within a U.S.-based Oracle Cloud Infrastructure (OCI) AI data center. For the Cloud Computing, High-Performance Computing (HPC), and Enterprise AI industry, this launch represents a major turning point: transitioning quantum processing out of specialized physics labs and embedding it directly alongside classical AI workloads in public cloud environments.

The News: Bringing High-Fidelity Quantum Processing into the Cloud Mainstream

The core technological breakthrough behind the collaboration is the deep integration between Quantinuum’s trapped-ion hardware and OCI’s high-speed cloud network. Rather than forcing enterprise research teams to procure, install, or operate dedicated cryogenic and optical hardware on-premises, OCI customers will be able to access Helios as a managed cloud service.

Also Read: Nutanix Puts Agentic AI into Action for Enterprises with Model Context Protocol Integration

Key technical highlights of the integrated OCI Quantum Service include:

High-Fidelity Trapped-Ion Hardware: Helios, Quantinuum’s third-generation quantum computer, features a 98-physical-qubit trapped-ion architecture capable of operating 48 logical qubits. The system achieves an average two-qubit gate fidelity of 99.921%, surpassing the critical “three 9s” accuracy threshold required for reliable enterprise quantum operations.

Extreme Energy Efficiency: While top-tier supercomputers routinely consume between 16 to 39 megawatts of electricity, a single Helios system operates at roughly 60 kilowatts drawing less than 1% of the power needed by traditional supercomputers for targeted mathematical workloads.

Hybrid Quantum-Classical Programming: Oracle plans to preview the service in the coming months, offering open-source hybrid programming frameworks that allow software engineers to combine Quantinuum’s development tools with native OCI compute, storage, identity, and GPU fabrics.

Transforming the Cloud Computing and Enterprise IT Sector

Integrating commercial quantum systems into major public cloud networks signals a fundamental evolution in how enterprise cloud providers design their technology stacks.

The Convergence of Quantum, AI, and Classical HPC
Historically, cloud computing vendors treated AI models, supercomputing clusters, and quantum experiments as distinct technology silos.

The Quantinuum – Oracle alliance highlights the market shift toward tri-hybrid computing. As foundational AI models expand in scale, using quantum hardware to solve specific sub-problems such as high-dimensional matrix optimization, molecular state simulation, or feature mapping—will allow classical GPUs to operate with far higher efficiency. Cloud platforms will increasingly be evaluated on how fluidly they pass data between GPUs, classical CPUs, and quantum processing units (QPUs).

Lowering Capital Barriers to Commercial Quantum Adoption
Before cloud integration, deploying quantum computing required multi-million-dollar capital investments, specialized facility management, and bespoke software pipelines.

Delivering Helios as a cloud-hosted service on OCI democratizes access. Organizations can explore quantum-classical algorithms on a pay-as-you-go basis under the same identity, governance, and security models they already use for their everyday cloud operations.

Broad Operational Impact on Enterprise Businesses

For commercial businesses operating in research-intensive sectors, the availability of managed hybrid quantum compute delivers direct strategic and financial advantages:

De-Risking R&D While Cutting Compute Costs
Building in-house quantum infrastructure is cost-prohibitive for most corporations. Utilizing OCI’s managed quantum service allows enterprises to de-risk technological innovation, test quantum algorithms on real hardware, and scale compute resources on demand while managing capital expenditure.

Preparing Organizations for the Post-Quantum Era
As quantum hardware matures toward full fault tolerance, organizations that fail to build quantum-literate engineering teams risk falling behind. Cloud-accessible quantum-AI environments provide enterprise engineering teams with a practical environment to build proprietary intellectual property today, ensuring a smooth transition into the era of quantum-accelerated business velocity.

The post Quantinuum and Oracle Partner to Bring Hybrid Quantum Computing to Oracle Cloud Infrastructure appeared first on ITDigest.

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Highlighting the strategic evolution of industrial automation, Amit Chadha, Chief Executive Officer & Managing Director, L&T Technology Services, said, “The next phase of Engineering Intelligence will be defined by how effectively autonomous AI agents collaborate to solve complex industry challenges across engineering, production and customer experience. Over the years, LTTS has built AI-powered engineering solutions that address domain-specific business problems across industries. With AgenticIQ, we are transforming these proven capabilities into reusable AI agents on a unified Agentic AI platform that enables enterprises to rapidly build, orchestrate and deploy next-generation agentic solutions at scale.” Ultimately, this platform equips global industrial enterprises to deploy trustworthy, scalable AI without compromising proprietary domain knowledge or operational reliability.

Read More: L&T Technology Services Launches AgenticIQ, an End-to-End Agentic AI Platform for Engineering, Manufacturing and Customer Experience

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