Thanks to this development, banks across the globe can get an even wider variety of Temenos applications as SaaS on AWS, including not just digital banking and payment services but also the core banking platform. The combined package aims to assist financial institutions in modernizing their operations while giving them the liberty of choosing how they want to adopt cloud technologies. Firms can either implement the modules separately, deploy a full enterprise solution, or integrate Temenos with their existing infrastructure.

This decision represents an increased move in the sector toward banking architectures that are cloud-native and modular so that financial institutions can react more quickly to continuously changing customer expectations and regulatory requirements. Banks, by moving technical management to SaaS environments, have more time for product innovation, customer engagement, and efficiency in operations.

Also Read: Rafay Systems Launches Token Factory to Help GPU Providers Monetize AI at Scale

Barb Morgan, Chief Product & Technology Officer at Temenos, said: “We’re delighted to expand our Temenos SaaS offering on AWS, further strengthening our SaaS capabilities and giving banks greater flexibility in deploying Temenos solutions as SaaS in line with their technology strategy and market requirements.”

AWS leaders argued that this partnership allows banks the freedom to change their ways gradually without sacrificing the enterprise-level growth and security that are a hallmark of their operations. Scott Mullins, Managing Director for Worldwide Financial Services at AWS, highlighted that through this significant development, banks can introduce new functionalities either gradually or go through a total transformation.

Market experts also recognize this improvement as part of a broader inclination towards composable banking ecosystems. According to David Albertazzi, Executive Advisor & Director of Retail Banking & Payments Practice at Datos Insights, diversifying a cloud-based banking platform is a move that is driven by a desire for more flexibility while ensuring the very important aspects of compliance, security, and data sovereignty are met.

Temenos and AWS have worked together since 2019 and currently support financial institutions ranging from traditional banks to digital-first challengers across multiple global markets. Existing deployments include organizations such as MidWestOne Bank, Credem, WeLab Bank, and ila Bank.

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The launch marks a major milestone in Source Support Services’ evolution as organizations race to meet the demands of the AI, supercomputing, and hyperscale data center economy. Built on decades of experience delivering outcomes in mission‑critical environments worldwide, the Unified Services Platform enables data center builders, operators, and technology manufacturers to rapidly scale execution across critical power, cooling, and large‑scale technology deployments.

Source Support’s vision is clear: to orchestrate the world of work at scale. The Unified Services Platform represents the evolution of that vision, bringing together technology, talent, and execution into a single, integrated ecosystem built for the accelerating demands of artificial intelligence, data center expansion, and next‑generation original equipment manufacturing (OEM) technologies.

Also Read: Rafay Systems Launches Token Factory to Help GPU Providers Monetize AI at Scale

As AI‑driven capacity requirements intensify and OEMs scale production of mission‑critical equipment, organizations face growing pressure to execute flawlessly across highly distributed, multi‑stakeholder environments. Fragmented service models, disconnected systems, and siloed workflows increase risk, delay delivery, and drive cost overruns across complex projects.

Designed and operated in alignment with ISO-aligned processes, the Unified Services Platform consolidates everything required to design, staff, train, execute, and measure global field service operations into a single integrated environment. Capabilities include work order management, certified technician dispatch, credentialing and compliance, real-time service tracking, parts logistics, quality control, and executive-level reporting, delivering real‑time visibility, disciplined execution, and predictable outcomes at global scale.

“We’ve built the service delivery operating system for the data center buildout economy,” said James Kirby, CEO of Source Support Services. “The Unified Services Platform is a human-centered, Salesforce‑native platform that orchestrates the world of work at scale, backed by a global network of credentialed trades, skilled labor, and IT service professionals operating at the center of the most significant infrastructure investment cycle in a generation.”

Kirby added, “From advanced cooling technologies, including air, liquid, and immersion systems that remove heat loads from the data center floor to the OEMs designing and building the mission‑critical technologies behind it, today’s data center environments demand flawless execution. After 25 years of delivering global IT services, our focus is bringing discipline, coordination, and human‑centered execution to the entire ecosystem.”

Source: BusinessWire

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This is a response to a gap between AI technology and enterprise readiness. While most enterprises are investing heavily in AI technology, many are failing to achieve significant returns on investment due to outdated operating models and governance structures. Agentic Service Management will bridge the gap between AI technology and enterprise readiness by aligning IT service management with AI-native technology.

“Most enterprise environments were built for people running tickets and tools, not for fleets of autonomous agents executing tasks across hybrid and multi-cloud estates—and this mismatch is limiting AI from moving out of pilots to outcomes,” said Kris Lovejoy. “You can’t scale agentic workflows on top of operating models that were designed for manual work.”

The solution includes a maturity assessment delivered through Kyndryl Consult, enabling organizations to evaluate their readiness across service management, AI governance, security, and operations. Based on this assessment, enterprises receive a phased roadmap to adopt agentic IT service management responsibly, with guardrails and human oversight. Additionally, Kyndryl Agentic AI Digital Trust provides a security-first framework to manage risk, compliance, and governance across AI-driven workflows, particularly in regulated industries.

Kyndryl is also applying these capabilities internally through its Kyndryl Bridge platform, enhancing operational intelligence and automating service delivery. The company already executes nearly 200 million automations monthly, demonstrating the scale at which agentic AI can transform IT operations.

Also Read: Armada and Microsoft Partner to Deliver Sovereign AI at the Edge with Azure Local

Implications for the IT Industry

Kyndryl’s statement is a sign of the IT industry’s wide-ranging change to AI-native service management and autonomous operations. IT service management (ITSM) models built around ticketing systems and manual workflow operations are becoming less and less compatible with the speed and complexity of modern AI-driven environments. Agentic service management is a hint of the future of systems of execution, where AI agents perform tasks such as infrastructure management, issue resolution, and operational optimization in real-time.

IT leaders must now commit to AI governance, orchestration, and operational transparency as this evolution brings along with it new priorities. On the one hand, enterprises should develop IT architectures for continuous, autonomous decision-making without compromising the regulatory compliance that e.g. ISO 42001 requires. On the other hand, implementing AI governance frameworks, integrating real-time monitoring systems, and policy-driven controls into the core infrastructure is a challenge.

The increasing role of AI digital trust frameworks only underscores the fact that we have to find ways for security and accountability to co-exist with innovation. IT teams are also seeing their roles radically transformed by the coming together of AI, cloud and IT service management. Rather than tracking tickets and manually working on infrastructure, IT professionals will progressively be monitoring AI-driven systems, their chief concerns being strategy, governance and performance optimization.

Business Impact and Strategic Value

For businesses, Agentic Service Management can be a game-changer. They can greatly improve their efficiency and agility by automating routine IT processes and resolving issues in real time. Organizations will be able to reduce the amount of downtime, cut the costs of their operations, and make their services more reliable.

What’s more, being able to roll out AI-driven workflows in hybrid and multi-cloud settings means quicker innovation. Companies can launch brand new applications, fine tune their infrastructures, and meet changing demands of the market with even more speed and accuracy.

Besides that, embedding governance and compliance frameworks make sure that the usage of AI won’t compromise security or regulatory compliance. This holds very true especially for industries such as banking, health care, and government, where data protection and compliance are of utmost importance.

Enabling the Future of Autonomous IT

Kyndryl’s Agentic Service Management solution is a testament to the defining trend in enterprise technology today: the move from manual IT operations to autonomous, intelligent service ecosystems. With its solution offering a framework for the implementation of agentic AI, the company is helping organizations move from proof-of-concepts to business outcomes.

As enterprises continue to leverage AI at scale, solutions like this will play a crucial part in helping organizations evolve from being mere enablers within the enterprise to being strategic business differentiators for innovation, efficiency, and competitiveness.

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Google Gemini Gems allow users to build personalized AI assistants by adding instructions and internal content like documents, PDFs, and internal data to AI tools. Although this has improved productivity, it has also opened new security risks for organizations, especially when users share these gems, even if they do not have direct access to the original content. This has created a new problem, considering that gems use underlying files to respond to users, and when they are shared, they expose internal data to unauthorized individuals.

In response to this new security risk, DoControl has incorporated Google Gemini Gems into its security framework, considering them core assets within Google Drive environments, allowing IT and security teams to monitor them with similar control levels to other critical data resources.

Also Read: Securitas Strengthens Digital Security Portfolio with Acquisition of Liferaft, a Leading SaaS Threat Intelligence Platform

With the new capabilities, organizations can monitor the creation and sharing of Gems, evaluate the risks of the associated data, and maintain a record of access and exposure events. Organizations can now use the platform to enforce policies automatically, including revoking or restricting access and sharing of Gems, blocking the sharing of Gems with the outside world, and setting up temporary permissions to minimize potential risks.

“Google Gemini Gems represent a powerful shift in how work gets done, but they also introduce new and often invisible data risks,” said Tamir Passi, VP of Product at DoControl. “Because this is such a new capability, organizations don’t yet have established security practices around it. We moved quickly to address this new risk, as we do with all emerging threats. Our goal is to continuously deliver visibility and control so that as new innovations emerge within Google Workspace, our customers can confidently adopt AI tools without compromising their security.”

The launch is a reflection of a wider industry move to protect AI-driven workflows, especially as organizations increasingly integrate generative AI into everyday business. With its extension into new AI assets such as Gemini Gems, DoControl is seeking to help organizations balance innovation and strong data protection.

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Healthcare Security Requirements

To meet HIPAA mandates, the company adopted an on-prem deployment supported by AccuKnox. By implementing Application Security Posture Management (ASPM) with DAST scanning, AccuKnox delivered risk prioritisation and automated compliance.

Why Humata Health Chose AccuKnox

After evaluating multiple vendors, Humata Health selected AccuKnox for its:

• Unified ASPM for Azure DevOps
• On-prem deployment for HIPAA compliance.
• Integration with GitLab and Azure DevOps.
• Fast, coordinated execution across Sales, Product, and Leadership.

During the proof of concept, AccuKnox showcased how ASPM delivers actionable insights, automates compliance, and provides unified visibility across cloud environments.

Also Read: Cyclr Launches MCP PaaS Innovation for AI Connectivity

Leadership Testimonials

“At Humata Health, securing our customers’ data is critical,” said Duy Dang, Director of Information Security & IT, Humata Health. “AccuKnox’s ASPM and CNAPP capabilities allowed us to enhance our application security posture quickly and effectively. The team’s responsiveness and technical guidance made the deployment seamless and impactful.”

“We are thrilled to partner with AI-powered HealthTech leader Humata Health to enhance the security of their software development lifecycle,” said Brian Laing, CSO, AccuKnox. “Through our Application Security Posture Management (ASPM) capabilities – including full Azure DevOps and GitLab integration – Humata Health gains unified visibility and control across its CI/CD pipeline.”

“This win showcases how alignment, agility, and customer-first execution drive real outcomes,” said Emre Kulali, VP of Strategic Partnerships, AccuKnox. “Humata Health’s trust in our ASPM and CNAPP capabilities reaffirms our commitment to enabling secure innovation for healthcare organisations worldwide.”

Source: PRNewswire

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Headquartered in Halifax, Canada, in 2014, Liferaft is known as a prominent SaaS-based Open-Source Intelligence (OSINT) threat solutions provider. The company has established itself in the fast-growing multi-billion US dollar threat intelligence industry by catering to hundreds of large enterprise customers across North America with scalable risk intelligence solutions.

As of the end of 2025, Liferaft had subscription-based annual recurring revenue (ARR) of MSEK 138 (noting a value of approximately USD 15.3 million) with organic growth of over 30%.

Strategic Rationale and Growth Potential

In a statement outlining the strategic logic behind the acquisition, Securitas President and CEO, Magnus Ahlqvist, emphasized the importance of digital risk intelligence in modern security programs:

“During the last few years, we have strengthened our value proposition and profitability in our guarding business, developed a globally leading position in technology and built a more modern and digital business. As the threat landscape becomes more dynamic, we see a growing need from our clients for digital risk intelligence solutions that enable more proactive security programs. Having partnered with Liferaft for five years, we know their capabilities well and see a strong strategic and cultural fit, as well as the significant intellectual property (IP) their solutions bring to our portfolio”.

Also Read: Palo Alto Networks Unveils Quantum-Safe Security to Future-Proof Enterprise Cryptography

Ahlqvist further highlighted the value Liferaft brings to Securitas’ recurring revenue model: “The acquisition creates significant opportunities to apply Liferaft’s threat-intelligence capabilities and proprietary IP across our client base. It also contributes to the development of a more scalable Securitas and strengthens the growth of our high-margin recurring monthly revenue business, which today exceeds BSEK 1”.

Platform Capabilities and Client Impact

Liferaft’s flagship platform continuously and automatically aggregates threat data by monitoring global public sources around the clock. This enables clients to maintain a dynamic and real-time understanding of their threat landscape, with advanced analytics and visualization tools that support rapid validation, team collaboration, and enterprise-wide distribution of actionable intelligence.

Key platform features include:

• 24/7 monitoring of global threat vectors
• Automated threat data aggregation and advanced analytics
• Real-time risk alerts for rapid stakeholder notification
• Collaborative and visual reporting tools that accelerate decision-making

These capabilities align with growing market demand for proactive, integrated security insights that empower organizations to anticipate and react to threats before they escalate.

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Also Read: Zenity Launches End-to-End AI Agent Security on AWS Marketplace

“Organizations have made major investments in SaaS, but most still have very limited visibility into how those applications are actually configured and where silent risk is building up,” said Paul Martini, CEO of iboss. “With SSPM, iboss uses AI to translate complex SaaS settings into clear, prioritized actions, so security and IT teams can continuously reduce exposure, align with Zero Trust principles, and demonstrate real governance over the SaaS platforms that run their business with AI-powered clarity and speed.” By embedding SSPM into the iboss SASE platform, companies can transition from static reports to continuous risk measurement, reduce operational overhead, and better communicate SaaS-related exposure and governance to executives, auditors and regulators.

Read More: iboss Enhances AI-Powered SaaS Security Posture Management to Reduce Hidden SaaS Risk

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In Cyclr’s analysis of MCP adoption, 9.4% of 460 monitored SaaS platforms released a native MCP solution in 2025 – concentrated largely among large enterprises with the resources to engineer secure AI interoperability. Cyclr MCP PaaS is designed to make that capability achievable for SaaS companies of any size, enabling them to publish customer-facing MCP Servers in minutes and offer them through an embedded, in-product marketplace experience.

With Cyclr’s MCP PaaS a SaaS company can produce and publish a new customer facing MCP Server within minutes.

“Yet again, as we did with embedded iPaaS, I’m delighted to announce a major innovation in the connectivity space,” said Fraser Davidson, CEO of Cyclr. “SaaS products are quickly becoming critical data sources for AI agents. Delivering that interoperability securely should not demand a multi-quarter rebuild. Cyclr MCP PaaS gives product and engineering teams a practical path to become AI-ready, launch MCP Servers within minutes, and create new revenue opportunities as the agent economy accelerates.”

Also Read: AtlasNova Raises $2.3M to Transform Small Biz Automation 

Built on Cyclr’s established embedded integration platform, MCP PaaS brings enterprise-grade data processing and security to MCP delivery, including multi-tenant isolation and governed operations.

“MCP is the architectural foundation that helps agents translate human intent into product actions,” said Nic Butler, CTO of Cyclr. “At scale, that requires tenancy boundaries, access control, and auditability. Cyclr MCP PaaS provides a governed runtime for MCP Servers with templates, an embedded marketplace experience, and unified monitoring so teams can move fast without sacrificing control.”

Cyclr MCP PaaS enables SaaS companies to:

• Ship faster: Launch MCP Servers in minutes via a standardized approach.
• Support customer-specific needs: Adapt to custom objects and fields without bespoke rebuilds.
• Monetize safely: Offer premium AI capabilities and usage-based tiers with governance, including OAuth 2.1, RBAC, data minimization, endpoint packaging, and full audit trails.

Source: Globenewswire

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At its core, Deductive AI is a unified platform for deploying and training AI agents that connect to an organization’s code, logs, metrics, traces, and events. These agents can reason over a continuously updated knowledge graph that maps relationships across systems, allowing them to test hypotheses, evaluate evidence, and surface precise root causes in seconds.

“The complexities and inter-dependencies of modern infrastructure means that investigating the root cause of an outage or incident can feel like searching for a needle in a haystack, except the haystack is the size of a football field, it’s made of a million other needles, it’s constantly reshuffling itself, and is on fire – and every second you don’t find it equals lost revenue,” said Sameer Agarwal, co-founder and CTO of Deductive AI. “Our goal is to fundamentally change this problem of how engineers troubleshoot software in production. By teaching AI agents to think like engineers, we’re giving teams time back to build and innovate rather than constantly firefight.”

Engineering teams today face the overwhelming challenge of diagnosing software failures across fragmented systems, sifting through petabytes of logs, millions of time-series metrics, and hundreds of dashboards to find the needle in the haystack. These investigations can take hours or days, diverting engineers from building new features and shipping products while outages ripple through systems long after the initial fault.

“We’ve seen world-class engineers spending half of their time debugging instead of building,” said Rakesh Kothari, co-founder and CEO of Deductive AI. “And as vibe coding generates new code at a rate we’ve never seen, this problem is only going to get worse. With new unpredictable failures, teams that don’t evolve their approach to debugging are going to stay stuck maintaining instead of shipping.”

Powered by purpose-built agentic AI and reinforcement learning, Deductive mimics the workflow of experienced Site Reliability Engineers (SREs). It generates hypotheses, tests them against real system evidence, and provides clear, actionable insights at every step of an investigation. While traditional observability tools stop at surfacing problems, Deductive AI takes it a step further by not only pinpointing root causes but also providing fixes and guiding teams through remediation.

Also Read: NMI Unveils Developer-First Platform for Easier SaaS Payments

“Our Ads Platform operates at a pace where manual, slow-moving investigations are no longer viable. Every minute of downtime directly affects company revenue. In those high-stress, ambiguous early moments of an incident, AI-driven triage plays a crucial role in accelerating our path to mitigation, supporting our 2026 goal of a 10-minute resolution window. Deductive has become a critical extension of our team, rapidly synthesizing signals across dozens of services and surfacing the insights that matter within minutes.” – Shahrooz Ansari, Senior Director of Engineering at DoorDash

“While the industry raced toward coding agents, our partnership with Deductive took a different path: bringing agentic AI directly into data operations. Together, we built a system that unifies our telemetry streams with Deductive’s reasoning engine, creating an AI-powered frontline agent that proactively manages our data pipelines detecting anomalies, diagnosing root causes, and accelerating resolution.” – Vikram Gundeti, Chief Technology Officer, Foursquare

“Deductive promises to democratise visibility into our training infrastructure that has a steep learning curve today. We are excited to partner with Deductive and believe it can automatically connect the dots across hundreds of workflow executions and point us to the root cause of any failed training workflow.” – Virajith Jalaparti Head of Infrastructure, Kumo

“We’ve been using Deductive for about a year now. It gives us the clarity and speed we need to turn telemetry and code data into meaningful action. Deductive has demonstrated ability to learn and adapt to our unique use case and provide the key insights at every step of the investigation for our team to move faster, smarter, and with confidence.” – Pratik Kotkar, VP of Engineering, Apoha

“Deductive AI is an industry-defining company tackling some of the most persistent pain points in software reliability. Their approach represents the next generation of intelligent reliability systems that help engineering teams move faster, innovate more, and manage complexity at scale.”– Max Gazor, Board Partner at CRV and early investor in category-defining companies such as Reflection AI, Airtable, and Cribl

Deductive’s founders bring deep expertise from building and scaling some of Silicon Valley’s most successful data and analytics platforms. Sameer Agarwal earned his Ph.D. at UC Berkeley, where he created BlinkDB, a state-of-the-art approximate query processing framework, and was among the first engineers at Databricks building Apache Spark. Rakesh Kothari was an early engineer at ThoughtSpot, where he led teams focused on distributed query processing and large-scale system optimization. Together, they founded Deductive AI to bring reasoning, not reaction, to the heart of software reliability.

Source: PRNewswire

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