Alternatives for teams whose blocker is the regulator
The AI-agent tooling market splits into three layers. Most evaluations go wrong by comparing across layers, so name your problem first:
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1. "We can't see what our LLM app is doing" → observability
LangSmith (deepest in the LangChain ecosystem) and Langfuse (open source, self-host-first) are excellent here. They trace, evaluate and analyse — they do not enforce anything.
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2. "Our model calls are unreliable or expensive" → gateway
Portkey puts routing, fallbacks, caching and cost controls in front of every provider with a one-line change. Guardrails live at the request level.
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3. "A regulator will ask us to prove it" → compliance runtime
This is EAIP's layer: consent, residency, policy and audit enforced in the execution path of every agent action, deployable inside your own AWS account in ap-south-1, with a hash-chained evidence trail built for DPDP, RBI and CERT-In (PMLA-aligned retention) scrutiny.
When NOT to pick EAIP
If you are an unregulated startup that wants tracing and prompt analytics for an app you already built, EAIP is more platform than you need — start with Langfuse (you can self-host it in an afternoon) and revisit when a bank, insurer or regulator enters the picture. EAIP itself is designed to coexist with these tools, not replace your observability stack.