Also Read: Nitro Launches MCP Connector for Claude AI to Streamline Enterprise Document Automation 

This helps organizations carry out their transformation strategies more effectively. “Many organizations have invested heavily in technology but struggle to see meaningful impact,” said James Watson, Chief Solutions Officer for CLA. “CLA One Digital is designed to bridge that gap, aligning people, processes, data, and technology so digital investments actually change how the business operates.” Built to support organizations across industries, the solution focuses on enabling practical adoption and measurable results rather than technology implementation alone.

Read More: CLA Launches CLA One Digital to Help Organizations Turn Digital Strategy into Measurable Outcomes

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Also Read: Lucid Software Brings Visual Collaboration into ChatGPT with MCP Integration

Nitro MCP addresses this challenge by connecting enterprise-grade document capabilities to Claude through a secure and reliable framework, allowing multiple document actions to be completed through a single AI prompt. As CTO John Fitzpatrick explained, “People want to use AI to help them get document-related work done more quickly, securely, and inside the tools they already use. The problem with most AI tools is that PDF and document operations are bolted on using whatever open-source libraries happen to be available.”

Read More: Nitro Releases MCP Connector for Claude AI, Introduces Document Automation Solution

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The announcement addresses one of the most urgent problems in enterprise AI. Outputs from AI assistants live in chat threads and documents, disconnected from the systems where work actually happens. Wrike MCP Server closes that gap. Built on the Model Context Protocol (MCP) open standard, it gives AI assistants like ChatGPT structured, real-time access to the Wrike Work Intelligence® Graph, which captures how complex work is done within organizations. The Wrike Work Intelligence Graph is the model of enterprise work, providing a rich semantic layer made up of projects, tasks, users, approvals, dependencies, risks, and other entities of the work domain.

Having processed more than 500 billion historical data points and more than five billion events annually, the Work Intelligence Graph provides AI assistants with the richest, most reliable foundation for enterprise work delivery available today. Every AI-driven action is permission-scoped, logged, and auditable. This commitment to practical, accountable AI deployment was recently recognized when Wrike Work Intelligence was named a winner of the 2026 Artificial Intelligence Excellence Awards, which spotlights the companies and leaders moving AI beyond experimentation and into real-world impact.

Also Read: Comcast Business Launches Innovation Lab to Accelerate Next-Gen Enterprise Solutions

“Wrike MCP Server gives enterprises a way to harness the AI tools their people already love, inside a governed layer that connects directly to our Work Intelligence Graph where execution actually happens,” said Thomas Scott, CEO of Wrike. “Governance earns autonomy, and autonomy enables scale. That’s how you turn AI into a scaled, governed competitive advantage.”

Wrike’s listing in the OpenAI GPT Store means enterprise teams can activate Wrike connectivity directly from the AI environments where they already work, no custom infrastructure, no engineering-intensive setup. OAuth 2.0 authentication uses industry-standard, secure protocols to meet enterprise needs. Each AI assistant gets its own revocable connection with defined permissions, and every action is attributable and auditable.

Wrike MCP Server is available at no additional cost for eligible customers. Key capabilities include:

• OAuth 2.0 authentication with user-scoped, revocable tokens and full audit trails
• OpenAI GPT Store listing for frictionless enterprise activation
• Real-time Work Intelligence Graph access across projects, tasks, custom fields, dependencies, and hierarchies
• Optimized token efficiency that reduces AI usage fees and delivers faster, more reliable responses
• Repeatable use cases, including status reporting, meeting-note-to-task conversion, work structure creation, and natural language search

“Our presence on the OpenAI marketplace means teams already standardizing on ChatGPT can connect to Wrike’s Work Intelligence Graph without friction,” said Alexey Korotich, CPO of Wrike. “The moment they do, their AI stops being a black box that generates disappearing or disjointed data and starts being a participant of collaborative workflows that are executed in a governed, audited, and trusted environment that Wrike provides. That’s the promise of trusted work delivery. It’s the confidence that work reaches the right outcome, faster, with clear accountability at every step.”

Source: BusinessWire

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Also Read: Connectbase Expands Its Footprint by Acquiring Cloud Age to Strengthen Its Operating System

This boosts productivity by merging Lucid’s visual tools with AI. It helps teams move from ideas to execution more smoothly. “The Lucid app for ChatGPT is yet another example of how Lucid is bringing the systems and context teams rely on into the AI tools they use every day,” said Jamie Lyon, Chief Product & Strategy Officer at Lucid Software. “When that context is readily available, teams can move faster and stay aligned. That’s where Lucid excels—bringing clarity to how teams work with AI so they can execute with confidence.”

Read More: Lucid Software integrates real-time visual context into ChatGPT with MCP server app

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This acquisition will help Accordion get a talented group of Salesforce professionals based not only in the United States but also in Europe, the Middle East, and Africa, as well as in India. Accordion will now be able to provide Salesforce solution implementation services in areas such as sales, services, pricing, and revenue management.

“The next phase of value creation in private equity will be driven by how effectively companies use technology, data, and AI to run their commercial operations,” said Nick Leopard, CEO of Accordion. “Salesforce sits at the center of that shift. By bringing A5 into Accordion, we’re expanding our ability to help sponsors and portfolio companies build scalable commercial infrastructure and stronger data foundations for growth.”

Also Read: Grid Dynamics and AWS Expand Strategic Partnership to Accelerate Data Foundations for Generative AI 

A5 contributes deep technical expertise across the Salesforce ecosystem, including Configure, Price, Quote (CPQ), Revenue Cloud, and core CRM platforms such as Sales Cloud, Marketing Cloud, and Service Cloud. These capabilities enable organizations to better manage complex pricing structures, streamline customer engagement, and gain improved visibility into revenue operations.

The integration also aligns with Salesforce’s growing focus on AI and data innovation. A5’s certified professionals in emerging technologies, including Agentforce, strengthen Accordion’s ability to deploy intelligent automation, enhance forecasting, and generate actionable insights from customer and revenue data.

In addition to expanding technical capabilities, the acquisition reinforces Accordion’s Salesforce Summit Partner status, the platform’s highest tier, reflecting its scale and implementation expertise.

“Private equity-backed companies need partners who can move quickly and scale with them,” said Mukesh Shah, Managing Director and Head of CFO Technology at Accordion. “With A5 joining Accordion, we’re adding significant Salesforce expertise while expanding our global delivery footprint, allowing us to support sponsors and portfolio companies more effectively as they build and scale their commercial platforms.”

By integrating A5’s capabilities, Accordion aims to help organizations transform CRM systems into strategic revenue engines, connecting financial, operational, and customer data to drive growth and long-term enterprise value.

The post Accordion Acquires A5 to Strengthen Salesforce, AI, and Global Delivery Capabilities appeared first on ITDigest.

Enterprise teams evaluating document agents now face a build-versus-embed decision. They can assemble their own stack by stitching together LLMs, document parsing and rendering, tool orchestration, and governance controls, then maintain it as workflows and compliance needs evolve. Or they can embed a pre-built, policy-governed agent designed for production document work from day one. First introduced in early 2025, Nutrient AI Assistant is deployed directly inside the Nutrient Viewer SDK users already rely on, where it benefits from high-fidelity document rendering and purpose-built document tooling rather than brittle, one-off integrations.

With this release, Nutrient introduces an agentic document editing agent to AI Assistant. This new reasoning layer is able to plan and execute multi-step workflows using Nutrient’s purpose-built document tools (rendering, structure-aware extraction, form operations, annotation, and redaction), while being governed by custom skills — reusable task definitions that encode domain-specific logic — and three-tier approval policies (autonomous, confirmation-required, or prohibited). Developers don’t have to stitch together parsing, chunking strategies, prompts, and brittle tool calls. They simply embed the SDK, configure rules and permissions, and get a document agent that operates with production-grade accuracy and compliance inside their product.

Also Read: Gamma Launches Gamma Imagine to Bring AI-Native Design to the Masses

For document-heavy organizations, this means an agent that interprets what employees need, applies pre-configured skills and business logic, and produces results tailored to how they actually operate. For the developers building those applications, it means an embeddable SDK with an autonomous editing agent they can configure with their company’s rules, workflows, and compliance requirements — connected to the LLM provider of their choice.

“Every enterprise we talk to is trying to solve the same problem: they need AI that works with their documents, not just reads them. But they also need it to run inside their own application, under their own rules,” said Jonathan Rhyne, co-founder and CEO of Nutrient. “We’re giving developers and the enterprises they serve a document agent they can embed, configure, and trust — one that operates inside their applications with the security and control their organizations expect.”

What’s new: the document editing agent

• Agentic execution inside the viewer: A reasoning layer plans work, selects tools, and carries multi-step document tasks through to completion using the viewer’s high-fidelity rendering and document structure.
• Observe, verify, adapt: The agent executes actions in sequence, observes results, verifies outcomes, and adjusts as needed across extraction, form filling, annotation, and redaction workflows.
• Staged changes with approval: Edits are staged for review and applied permanently only after approval, keeping humans in control of the final output.
• Policy-governed autonomy: Organizations define what the agent knows (skills), how it operates (context), and what it can do (approval policies) – from fully autonomous actions to hard prohibitions.
• Not a single-shot feature: A tool-using system designed to execute document work reliably inside the application where users already operate.
• Built for document-heavy industries

AI Assistant is designed for industries where accuracy, compliance, and auditability are critical, including:

• Legal: Extract liability caps and indemnification clauses from a contract, then stage redactions of client names for attorney review before permanent removal.
• Financial services: Read a receipt and populate an expense report automatically. Extract invoice line items or redact bank account numbers before audit sharing.
• Construction: Render a blueprint, extract door dimensions from the second-floor plan, pull window schedules from tables, and highlight fire-rated material references.
• Healthcare: Extract patient demographics from intake forms, summarize lab report findings with citations to specific pages, or redact PHI before sharing with research teams.
• Government: Identify personal identifiers across a public records request, stage redactions for review, and apply permanent removal on confirmation.

Your business logic, embedded in the agent

Document automation only creates value when it behaves the way a business operates. This is especially true in regulated, document-heavy work where “almost right” is a risk. Nutrient AI Assistant is built so organizations can apply their rules to every workflow and get consistent outcomes across teams, documents, and applications.

For developers, this means they can deliver that consistency inside their application without building and maintaining a bespoke document agent stack. They embed the Viewer SDK and configure governance controls so higher-risk actions follow prescribed approval paths, while lower-risk steps can run automatically. The result is workflow automation that matches how the business works and still fits the organization’s compliance and review model as requirements evolve.

Ultimately, Nutrient AI Assistant helps companies turn document work from a bottleneck into a repeatable, policy-aligned process that improves speed, reduces risk, and increases operational consistency.

Source: PRNewswire

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With many businesses investing in AI projects and initiatives, many have found it difficult to scale up their projects and achieve quantifiable ROI. The partnership is meant to help businesses achieve this through the provision of a structured framework that combines strategy, implementation of AI technology, and quantification of ROI. The partnership is meant to help businesses achieve this through the provision of integrated services such as operational benchmarking, workflow rationalization, AI-based automation, and improvement.

IBM Business Operations is going to share its knowledge of AI adoption such as automation platforms, AI engineering, and data-driven work- flows, whereas The Hackett Group will offer insights from its own proprietary benchmarks and best-practice framework The collaboration is geared toward assisting companies to map out where AI will generate the most valuable strategic outcomes, develop implementation plans, and measure the financial and operational effects of AI investment.

Implications for the IT Industry

The partnership between IBM and the Hackett Group is part of a wider change in the way the IT sector looks at the adoption of enterprise AIfrom pilot initiatives to strategies that are scalable and focused on business. Numerous companies have run into the major hurdles of enterprise AI success, which are data silos, disjointed technology stacks, and old business processes that are resistant to automation, among others. Bringing together advisory and technical implementation capabilities is an effective way to tackle these challenges from all angles.

Also Read: NinjaOne Revolutionizes Vulnerability Management with AI-driven Assessment to Reduce Risk Faster

To IT leaders, this alliance serves as a reminder that the IT department should have the entire range of capabilities, from one end to the other. Instead of centering the discussion around the development of the AI model or the experimentation phase alone, technology teams will also require working models with which they can unfold AI in the key business functions and derive performance metrics. Such are the teams that align IT, data science, operations and business strategy in a cross-functional collaborative effort.

Besides that, their collaboration highlights also the trend of AI orchestration and governance. As AI systems become more common in different functions, companies will have to ensure that the workflows are at the same time consistent, compliant, and aligned with their organizational goals. Benchmarking and best practice insights from The Hackett Group can assist IT departments to formulate standards to deploy, control, and optimize AI technologies in various environments.

This new agreement with the Hackett Group also reveals the increasing need for performance measurement and ROI transparency regarding AI implementation. In fact, CIOs and CTOs are still very much concerned about creating value, whether financial or operational. Having a good, organized framework for measurement and benchmarking enables companies to present a stronger case for AI investments to the boards and executive committees and, at the same time, it allows them to discover the performance improvement areas.

Broader Business Impact

For businesses across industries, the IBM–Hackett Group collaboration offers a practical pathway to transform AI from a standalone technology into a strategic driver of business outcomes. Many companies have invested heavily in AI pilots or point solutions that failed to scale due to lack of integration with business processes or unclear value propositions. By combining advisory insights with implementation expertise, the partnership helps organizations move beyond experimentation toward enterprise‑wide adoption.

One of the major advantages of this technique is discovering high-impact use cases – i.e. ways that AI could lead to measurable improvements like lowering costs, increasing productivity, enhancing customer experience, or generating more revenue. Through operational benchmarking, organizations can learn not only how they stack up against other companies but also where strategic changes in AI implementation might give them a competitive edge.

It’s a great partnership, especially considering the current economic slowdown, when business heads are highly focused on proving real outcomes of technology investments. Obviously, well-designed AI plans, systems for measuring performance, as well as data on operations give top managers solid, fact-based advice which helps them with making major decisions and distributing resources.

Future Outlook

The IBM Business Operations and The Hackett Group collaboration reflects a maturing enterprise AI market. As AI continues to permeate business functions, organizations are increasingly seeking partners who can provide not only technological innovation but also strategic guidance, performance measurement, and governance frameworks.

For IT leaders, the message is clear: successful AI adoption requires more than technical proficiency—it requires a holistic approach that aligns technology with business strategy, operational excellence, and measurable outcomes.

By enabling enterprises to harness AI more effectively and confidently, this partnership could help accelerate digital transformation efforts and unlock substantial value across industries in the AI era.

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Teams today face mounting pressure to produce more branded visual content, faster, and across more channels than ever. Legacy design tools have responded by bolting AI onto existing workflows, but Gamma Imagine is AI-native at its core. It’s designed to act like a human graphic designer, automatically applying a team’s brand colors and visual identity, with the ability to refine any output using natural language. Users can also upload a reference image to match a style across an entire creation. And while most AI image tools only offer a single output with limited control, Gamma Imagine presents users with multiple creative directions for each asset.

Additional key features of the launch include:

• AI-native, remixable templates: Start with any gamma created previously—or one of Gamma’s 100+ new professionally-designed templates—and simply describe the desired changes to get a personalized, fresh version instantly.
• Smart Charts: Build interactive charts and data visualizations, like bar charts, scatter plots, funnels, and heatmaps, that automatically inherit brand styling.
• AI Illustrations: Generate and revise branded illustrations, like logos, marketing assets, and social graphics, using natural language prompts.
• AI Infographics: Create on-brand infographics and diagrams from a text description, ready to use as a standalone asset or inside a presentation or document.

Also Read: Akkodis showcases real-world impact of AI innovation

Gamma is also expanding its integration ecosystem to meet professionals in the tools they already use. New integrations include ChatGPT, Claude, Make, Zapier, Atlassian, n8n, Superhuman Go, and Profound, with additional platforms like Glean coming soon. Users can now generate Gamma content, like presentations and documents, directly from their existing AI assistants and workflows.

“We built Gamma around the belief that anyone should be able to communicate visually without needing a design background or a design team,” said Grant Lee, CEO, Gamma. “This launch is the biggest expression of that vision yet, and with Gamma now living inside the tools where teams already work, the gap between an idea and a ready to share output is virtually nothing.”

To mark the launch, Gamma CEO Grant Lee is embarking on a global user tour, starting in Seoul, Korea on March 17, London, England on March 23, and São Paulo, Brazil on March 26. The tour reflects the international scale of Gamma’s user base: more than 80% of Gamma’s nearly 100 million users are outside the United States, making Gamma one of the most widely used AI creation tools on the planet.

Source: BusinessWire

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Appointment underscores next phase of growth and innovation for leading data and analytics solutions provider

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The new collaboration brings together cloud-native data and AI services of AWS with extensive expertise from Grid Dynamics in data engineering, analytics, and machine learning. This partnership will enable enterprises to take their generative AI efforts all the way from experimentation to production-scale environments.

As an established AWS partner with deep technical capabilities and demonstrated customer success management, Grid Dynamics is poised to help organizations through this transition-from proof-of-concept to real, operational AI deployments that deliver measurable business value.

Also Read: LambdaTest and SVAM International Ink Strategic Partnership to Revolutionize Enterprise Quality Management 

“We are thrilled to be a part of the AWS Data Foundations for Generative AI Program,” said Ilya Katsov, CTO, Americas at Grid Dynamics. “Data Readiness is the key to success in Generative AI. In this context, we help organizations solve pain points in data ingestion, model refinement, and deployment so that generative AI investments guarantee meaningful, scalable outcomes for our customers.”

Under the terms of the SCA, Grid Dynamics will deliver customized solutions at every stage of the generative AI lifecycle, including:

• Conducting data strategy and readiness assessments to evaluate organizational preparedness for generative AI adoption.

• Deploying accelerators and frameworks that make rapid implementation of robust data infrastructure workloads on AWS.

• Providing end-to-end AI solutions that refine models, targeting practical scalability.

• Regular optimization: monitoring and improving data and AI operations continuously.

Grid Dynamics has extensive experience in empowering customers from various industries, such as retail, manufacturing, and financial services, to leverage generative AI for the creation of hyper-personalized experiences, process automation, and data-driven decision making.

Grid Dynamics has Advanced Tier status with AWS as a Consulting Partner, backed by over 550 AWS-certified engineers and five recognized AWS competencies, including Data & Analytics and Machine Learning.

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