Ankur A. Patel
@aapatel09
CEO @Multimodal. Agentic AI for regulated financial workflows. Posting what we learn building agents that handle real loan files in production.
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Most agentic AI demos are easy. Production agents in credit union and community bank lending workflows are hard.
They need evals that test the whole workflow, not just the final answer. Regulation. Auditability. Document understanding. Exception handling. And a clear sense of when to stop and hand off to a human.
That last part is the whole game. A 95% extraction score still fails if the agent can't tell which 5% to flag for a loan officer.
So we build the boring parts: logs, evals, permissions, rollbacks, human review queues.
The boring parts are the product.
Building this at @MultimodalAI. Following along here.
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The finance ops problem nobody talks about:
Your best analyst isn't slow because they're bad.
They're slow because they spend 60% of their day pulling data from systems that don't talk to each other, formatting it into templates, and waiting for approval chains that haven't changed since 2004.
The bottleneck isn't intelligence. It's plumbing.
That's what we're fixing. @MultimodalAI
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The current wave of AI is human-to-agent: you ask, it answers.
The next wave is agent-to-agent: one agent completes a step, hands off to another, and the workflow keeps moving.
That’s the trend I’m most excited about: orchestration.
—>The reason is simple, business workflows don’t happen in one system.
They span tools, teams, vendors, and data sources. And most of the friction is coordination.
The real unlock is when agents can synchronize across that complexity: passing context, triggering actions, and collaborating even when they’re not built by the same company.
That’s what turns “AI features” into “AI operations.”
If you could automate one cross-tool handoff end-to-end, what would you pick?
#AiFuture# #Aitrend#
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