Guide

How to Choose an AI Agent Platform

About a week of evaluation for an enterprise team

Choosing an AI agent platform shapes the next 3-5 years of your AI infrastructure. This guide covers a practical evaluation framework — the questions that matter, the trade-offs to consider, and how LeafMesh ADK compares to the alternatives.

Steps

  1. 1

    List your requirements

    Vendor flexibility, deployment model (SaaS vs on-prem), compliance (SOC 2, GDPR, HIPAA, DPDP), governance primitives (audit, HITL, policy), observability, multi-agent support, and total cost. Rank them by criticality.

  2. 2

    Evaluate vendor lock-in

    Some platforms (e.g., IBM watsonx Orchestrate) are tightly coupled with one ecosystem. Others (LeafMesh ADK, agno.os) are vendor-agnostic. If you might use OpenAI, Anthropic, Google, or specialised models in the next 3 years, vendor-agnostic is non-negotiable.

  3. 3

    Evaluate governance primitives

    Does the platform provide audit, HITL, policy enforcement, and escalation as primitives — or do you have to DIY them? Frameworks like LangGraph and AutoGen are powerful but DIY for governance. LeafMesh provides governance primitives natively.

  4. 4

    Evaluate operational maturity

    Self-healing, cost control, capability routing, observability dashboards. These are operational primitives that separate research-grade from production-grade. Test them in a 2-week trial.

  5. 5

    Evaluate multi-agent support

    Single-agent platforms struggle when you need a team. Look for: shared memory, capability-based routing, cross-agent policy. LeafMesh treats multi-agent as the default; many platforms treat it as an extension.

  6. 6

    Run a 2-week pilot

    Pick one workflow with real stakes. Deploy on the candidate platform end-to-end including governance and observability. Document time-to-first-deploy, time-to-policy-update, time-to-debug-an-incident.

  7. 7

    Compare total cost

    Don't just look at platform pricing. Consider: development time, ops time, vendor lock-in cost, time-to-production. LeafMesh's published pricing (free → $4,500/mo Pro → custom) makes the platform side easy to evaluate.

Common pitfalls

  • !Choosing the platform with the loudest demos rather than the best operational primitives.
  • !Underestimating governance until you're in front of an audit committee.
  • !Locking to one LLM vendor — your model needs will change in 12 months.
  • !Skipping the pilot. You learn more in 2 weeks of real use than 2 months of evaluations.

Want to put this into practice?

LeafMesh ADK is the agent operations fabric that runs the patterns in this guide.

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