enterprise architecture
enterprise architecture at Beyond Market Intelligence is a file of 3 stories. The newest of them: “Architecting Trust: A Blueprint for Enterprise mDL Decisions”, “Capital One's open-weight models power a scalable multi-agent AI platform”, and “From Chatbots to Operational Intelligence: Building Agents That Scale”. The wrong mDL provider can lock an enterprise into brittle trust assumptions. Capital One isn't waiting for a better off-the-shelf model. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every enterprise architecture story on Beyond Market Intelligence, newest first.
Architecting Trust: A Blueprint for Enterprise mDL Decisions
The wrong mDL provider can lock an enterprise into brittle trust assumptions. Praveen Kumar Gopalakrishnan's framework cuts through that risk. It shows which cryptographic properties to verify, which trust boundaries must stay visible, and how requirements shift across real-world use cases. This is the blueprint for asking hard architectural questions before committing. For teams building smarter AI agents, our coverage of AWS's new open-source tools offers a complementary look at control and abstraction.
Capital One's open-weight models power a scalable multi-agent AI platform
Capital One isn't waiting for a better off-the-shelf model. At VB Transform 2026, Kel Vanee described how the bank built a multi-agent platform by deeply customizing open-weight models with proprietary data, treating that data as an advantage no frontier model can match. The approach scales beyond one use case, lifting performance across the portfolio. It's a practical blueprint for financial services, and for readers exploring how AI agents handle complex workflows, our related piece on bridging retrieval and action offers a useful parallel.
From Chatbots to Operational Intelligence: Building Agents That Scale
Enterprises don't fail to scale AI because the models aren't smart enough; they stumble on the messy reality of their own systems. Arun Joseph brings that truth to life with real-world lessons from scaling Deutsche Telekom's LMOS. He tackles the organizational fault lines head-on, advocates for replacing tool sprawl with core platform abstractions, and pushes beyond basic chatbots toward operational intelligence. His work with ephemeral agents and an Agent Definition Language makes this a practical, human-centered look at what's actually required.