We go live tomorrow at 9 AM PT. In one hour, @Simform and @Microsoft walk through activating a governed patient data estate in #MicrosoftFabric through #MicrosoftFoundry, and the six decisions that turn it into clinical intelligence. - Which clinical AI use case to start with - What your data has to support before it ships - Grounding outputs in trusted enterprise data with Foundry - Build or buy for the first deployment - Where human review belongs - How to sequence the use cases that follow If a governed data estate is still waiting on its first clinical #AIworkflow, join us live. Register: simform.com/webinar/unified-… 📅 Tomorrow, October 15 | 9–10 AM PT · 12–1 PM ET 🗣 Speakers: Ritesh Shah, Field CTO, Simform Chase Dixon, Cloud & AI Specialist, Microsoft #DigitalHealth #MSPartner

Simform has earned the Microsoft Azure Virtual Desktop specialization. This milestone validates our expertise in deploying, optimizing, and securing virtual desktop infrastructure on Azure. A desktop migration that leaves identity, networking, and security unchanged carries the same legacy limits into the cloud, so we align them under one modernization program. What does this mean for your business? - Scale your virtual workspace as workforce needs change, with host pools, identity, and networking designed using the Azure Well-Architected Framework. - Extend your Azure security controls into the desktop environment through least-privilege access and Microsoft Defender for Endpoint. - Manage cost and reliability after go-live with our 24x7 managed services and SimOps, our proprietary platform that tracks Azure consumption. As an Azure Expert MSP with ten @Microsoft specializations, we co-engineer virtual desktop modernization as part of your wider Azure environment. Read the full story here: simform.com/blog/azure-virtu…

An AI policy that sits in a document does very little when an agent finds a way around its rules. In the next #ECAFVoices episode, host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, sits down with Adrian S., Chief Information Security Officer (CISO) at a leading #healthcare workforce #technology company, to talk about guardrails that keep getting bypassed and the gap between writing governance and enforcing it. Watch the trailer for a first look! Full episode coming soon.

Thank you to everyone who visited us at Booth 17 during FabCon Europe 2026, and to everyone who joined the FabCon Pre-Game on Wednesday evening. Across four days in Barcelona, one theme came up again and again. Teams want a Fabric platform they can rely on in production, and they're starting to see governance as the thing that makes that possible rather than paperwork that slows them down. At the booth, we compared notes on: - Phased migrations planned around production schedules - TrueMorph in action: AI-powered data warehouse modernization - Making Fabric spend legible with capacity governance and FinOps - DataOps discipline that turns Fabric pilots into production platforms Thank you for spending time with us. We look forward to continuing these conversations.

@Simform has earned the Microsoft Solutions Partner designation for AI Business Solutions, completing our coverage across all Microsoft AI Cloud solution areas. We are now one of fewer than 50 companies globally to hold Azure Expert MSP recognition alongside all three Solutions Partner designations: Cloud & AI Platforms, AI Business Solutions, and Security. This milestone strengthens our ability to help enterprises move beyond isolated AI initiatives by connecting strategy, platform, governance, and execution across the Microsoft ecosystem. Through our Agentic Operating Model and Microsoft-aligned AI platform strategy, we help organizations redesign workflows, establish governance, and scale AI toward production outcomes. Read the full breakdown: simform.com/blog/simform-com… Thank you to our @Microsoft teams and our customers who continue to put these capabilities to work. #MSPartner #MicrosoftPartner

Healthcare can move data between systems and still lose the context that matters. Murali Vemulapalli uses a prescription refill to show where the friction appears: - The request can cross the provider, pharmacy, payer, & PBM - Eligibility may be checked repeatedly across those systems - One synchronization problem can turn a routine workflow into a delay Interoperability is not only about moving records. Context has to survive the journey. Muralidhar Vemulapalli, Chief Enterprise Architect / Acting CTO at Leading Managed Healthcare Industry, explains why context remains a hard Health Tech interoperability problem. Watch Muralidhar Vemulapalli and Rameshwar Balanagu's full conversation now: simform.com/podcast/enterpri…

Spend $5,000,000 to automate work that already costs $9 an hour? Or just hire more people at $9 an hour. That objection is where most enterprise AI business cases quietly die. Leaders debate models and budgets while the real constraint sits somewhere else entirely: nobody can say where the data is, and the use cases are being picked by guesswork. In the third episode of ECAF Voices, Brandon Micci, Head of AI Strategy & Business Transformation at J.P. Morgan, joins host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, for a conversation that names the parts most teams would rather not audit: - Why the productivity everyone planned for has not arrived. - What a first AI use case actually costs in months before it clears governance. - Where AI fails when it is dropped into a platform people already avoid. - And why the work being automated first is the work that produces your next leaders. Here's the teaser. The full episode drops soon. #ECAFVoices

AI risk changes when one failure pattern can operate at enterprise scale. Murali Vemulapalli explains why autonomy, governance and control have to evolve together. Watch the complete ECAF Voices conversation in the full episode: simform.com/podcast/enterpri… #EnterpriseAI #AIGovernance

When a human makes a bad decision, it does not go viral. When AI makes one, it does. Muralidhar Vemulapalli argues the governance to meet that standard does not exist yet. Episode 2 of ECAF Voices, our Enterprise Cloud and AI Forum series, is now live. Rameshwar Balanagu, Co-Founder at Dallas CTO Club, sits down with Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at a leading managed healthcare company, on why the risk in scaling AI is the million instances that repeat a bad decision, not the single incident. Murali brings 25 years of health tech across large payers. He walks through what he calls Layer 6, his governance and observability layer, and separates human in the loop, human on the loop, and high agency. His warning: leaders who treat AI governance as somebody else's job carry the implications personally. The conversation stays on how these decisions get made, not on tooling. Full episode: simform.com/podcast/enterpri… Where does your organization sit today: human in the loop, human on the loop, or high agency in narrow workflows?

When a human makes a bad decision, it doesn't go viral. When AI makes one, it does. That asymmetry is where most enterprise AI conversations fall apart. Leaders debate model accuracy while the real exposure sits somewhere else entirely: governance that hasn't caught up to the scale AI is being deployed at. In the next episode of ECAF Voices, Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at a Leading Managed Healthcare Industry, joins host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, for a conversation that gets uncomfortable in the right ways: - Why the scale of AI, not the individual incident, is what should concern you. - What happens when regulation moves slower than the technology it's meant to govern. - Where the margin of error goes to zero, and what that forces you to rethink. - And why AI governance is not somebody else's job. It's yours. Here’s the teaser. The full episode drops soon. #ECAFVoices

The pilot worked. That is usually where the real problem starts. Episode 1 of ECAF Voices, our Enterprise Cloud and AI Forum series, is now live. Rameshwar Balanagu, Co-Founder at Dallas CTO Club, is joined by Shuchi Agrawal, Head of AI Execution at SMBC Group, for a conversation about the execution gap: the distance between a demo that impresses a steering committee and a system a regulated business can actually run. Shuchi has spent 25 years building AI and data systems across aviation, global banking, and financial services. She maps the four specific points where enterprise AI programs break before they ship, and makes one point most teams learn the expensive way: token economics belongs in your architecture decisions, not in a budget review after the fact. The conversation stays on how those decisions actually get made rather than on tooling. The full episode is on the ECAF Voices page: simform.com/podcast/enterpri… Where is the execution gap widest in your organization right now: the data foundation, the integration work, or adoption?

Cloud and AI strategies are everywhere. Production systems that live up to them are not. That distance is the execution gap. It shows up between a boardroom decision and the platforms, data, governance, and operating models needed to make that decision real. ECAF Voices, the podcast from @Simform’s Enterprise Cloud & AI Forum, brings that gap into the open through candid conversations with leaders responsible for closing it. Hosted by Rameshwar Balanagu, Co-Founder of Dallas CTO Club, the upcoming series features Shuchi Agrawal, Head of AI Execution at SMBC Group; Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at Arkansas Blue Cross and Blue Shield; and Brandon Micci, Head of AI Strategy & Business Transformation at J.P. Morgan, and many more guests. The teaser offers a first glimpse of conversations grounded in real decisions: what it takes to move AI beyond experimentation, modernize the platforms underneath it, and build governance into execution. ECAF Voices is coming soon. Where does the execution gap show up most clearly in your organization: platform, data, governance, or operating model?

Read the full announcement here: finance.yahoo.com/technology…

Simform's TrueMorph, AI-native data modernization solution, has achieved Microsoft Azure IP Co-sell eligible status. This status lets Microsoft's own sellers identify TrueMorph for qualified co-sell opportunities, and gives enterprises a Marketplace-based procurement path for Fabric-led data modernization, with purchases applying toward existing Azure Consumption Commitments. Here is what this status is built on: - AI-powered data profiling, transformation, and quality checks, with built-in migration paths for legacy stacks like SSRS, SSIS, SSAS, OBIEE, OBIP, and Informatica Power Center - Governance embedded at every layer, backed by Azure Key Vault, Microsoft Entra ID, Purview, Unity Catalog, and Azure Monitor We recently used TrueMorph to help a multi-region retail and vending operator unify 400 to 500 GB of scattered operational data on Microsoft Fabric, cutting stockouts by 30% and speeding up deliveries by 20%. "With Azure IP Co-sell status, our TrueMorph solution is validated to work in the Fabric ecosystem, and it lets @Microsoft and @Simform field teams go to market together, which is what actually helps customers move faster," shared Juan Llovet de Casso, Cloud Solution Architect at Microsoft. Thank you to everyone at Simform who built and delivered this. #MSPartner #MicrosoftPartner

Microsoft’s $2.5B Frontier Company investment points to where enterprise AI is heading next. Not more pilots. Not more model shopping. Engineering. @Microsoft is embedding 6,000 industry and engineering experts with customers to co-design, deploy, and continuously improve AI systems around measurable outcomes. The important shift is the operating model behind it: Intelligence + Trust. Enterprise intelligence lives in proprietary data, workflows, expertise, and decision logic. And the trust comes from the architecture around it, comprising governed data access, context engineering, evals, observability, model routing, FinOps, human review, and IP protection. That is the same direction @Simform has been engineering toward. We have been building reusable foundations for this phase: 𝐓𝐫𝐮𝐞𝐌𝐨𝐫𝐩𝐡 to turn fragmented data into secure, AI-ready foundations; 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐌𝐞𝐬𝐡 to design governed agentic systems; and 𝐏𝐞𝐱𝐀𝐈 and 𝐂𝐨𝐝𝐞𝐓𝐨𝐨𝐥𝐬 to bring AI-native discipline across delivery, review, and modernization. The next phase of enterprise AI will not be won by the team with the most agents. It will be won by the team that can make enterprise intelligence compound safely, measurably, and inside production systems. That has always been an engineering problem first. #mspartner #microsoftpartner

As @Microsoft reduces the infrastructure friction for deploying AI agents, the architecture decisions that determine whether these agents operate reliably in production matter more, not less. At Build 2026, Windows 365 for Agents reached general availability within Agent 365, giving enterprises managed Cloud PCs for agents working across modern apps, legacy systems, and UI-driven workflows. Microsoft Foundry also expanded its runtime, evaluation, and governance capabilities, while Microsoft Execution Containers remained in early preview. The platform can provide execution, containment, and controls. It cannot decide who owns a cross-system process. An agent that works in a pilot can still fail in production if no one defines the accountable process owner, approval thresholds, or recovery path when a workflow crosses a CRM, ERP, and claims system. For high-consequence workflows, the more defensible pattern is bounded autonomy. Authority should expand only when actions are observable, attributable, recoverable, and proven through evaluation. The boundary should follow the consequence and reversibility of the action, not the capability of the model. @Simform uses 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐌𝐞𝐬𝐡 within agentic AI engagements to implement the orchestration, access, observability, and governance controls behind those decisions. Skip this work, and the risks surface later as audit gaps, unreliable approval paths, and substantial rework before workflows can scale. #microsoftpartner #mspartner

Most enterprises do not have a data platform problem. They have a fragmentation problem. Here’s exactly how #MicrosoftFabric is designed to solve it: - Fabric consolidates services that used to run separately, like Data Factory, data science workloads, and Power BI, into one SaaS platform with a single billing architecture and shared compute - OneLake sits at the centre as a unified storage layer built on the Delta open table format, enabling lakehouse, data warehouse, and ML use cases from the same foundation - Native governance through Microsoft Purview and real-time intelligence through Event Hub come built in, not bolted on One platform. One storage layer. One place to govern it all. Anamika Shaw, Sr. Data Architect at @Simform, Rachael Villalaz, Cloud & AI Specialist at @Microsoft, and Matthew Wendel, Principal Solutions Consultant at @Simform, break down how manufacturing and retail organisations can modernise their data estates using Microsoft Fabric. Watch the full session here: simform.com/lp/webinar-moder… #MSPartner #MIcrosoftPartner

Clean data does not automatically make enterprise AI reliable. @ISG_News reports that more than half of organizations still struggle with legacy data residing in old applications, compounding the overall data silo issue and creating further roadblocks to value from AI. But modernizing pipelines alone does not resolve every data problem. Consider "active customer." If three business units define it differently, an agent querying enterprise data has no authoritative meaning to reason against. It can retrieve more records and still return conflicting answers that require manual verification. That is why semantic governance must be part of data-platform modernization, alongside data quality and ETL improvements. On #MicrosoftFabric, Power BI semantic models can expose governed measures, relationships, and business terminology within a domain. Fabric IQ ontology can extend those definitions across domains, although it remains in preview and currently requires external change-management controls. The practical sequence is smaller than an enterprise-wide ontology program: - Start with one agent use case. - Identify the entities it must interpret. - Assign authoritative definitions and owners. - Then test the agent against verified business questions before expanding. Without a governed business meaning, better data access can widen an agent’s reach without improving its reliability. The hidden cost shows up in continued human verification.