Last updated August 2026·2 agencies reviewed·How we rank
AI agent development companies build software that takes multi-step actions on its own: reading a request, calling tools, deciding what to do next, and handing off to a person when it cannot finish. This is a harder engineering problem than workflow automation, and the gap between firms that have shipped agents to production and firms that have demoed them is wide.
We weighted evaluation and observability heavily here. An agent without tests and traces is a prototype, whatever it is called in the pitch deck.
Best forRegulated industries needing auditable AI agents
Kestrel is the pick when an agent has to survive an audit. Every engagement ships with an evaluation suite and full tracing, and their default posture is to route uncertain cases to a human rather than let the agent guess. That rigour costs time: their discovery phase alone runs three to four weeks, which is slow if you are trying to prove a concept quickly.
Pros
Evaluation suite and tracing included as standard
Deep experience with audit and compliance constraints
Clear escalation design for low-confidence cases
Cons
Discovery alone runs 3-4 weeks before any build starts
Best forProduct teams embedding agents in their own software
Cadence is the right call when the agent is part of the product your customers use, not an internal tool. They work like a product engineering team: evaluation harnesses, staged rollouts, real telemetry. The narrow part is the stack. They are TypeScript-first and will push back on anything that pulls them into a Python data platform, which rules them out for a good number of teams.
Pros
Product-grade engineering practice with staged rollouts
Evaluation harness and telemetry from day one
Comfortable with customer-facing, high-volume agents
Cons
TypeScript-first, a poor fit for Python data platforms
An automation follows a path you defined in advance. An agent decides its own next step at run time, calling tools until it reaches a goal or gives up. That flexibility is the point and also the risk, which is why production agents need evaluation suites, tracing and a human handoff.
What should I ask an agent development company?
Ask how they evaluate the agent, what happens when it fails, what the human handoff looks like, and what it costs per run at your expected volume. If they cannot answer the cost-per-run question, they have not run one at scale.