# AI Agents & Agentic Development

> Custom AI agents and multi-agent systems that retrieve context, reason, call your tools, and verify their own work. Production-grade agentic development.

Custom AI agents and multi-agent systems that retrieve context, reason through a task, call your tools, and check their own work, with humans gating the high-stakes moves.

## Chatbots answer. Agents act.
Most teams have wired a language model to a chat box and called it automation. It answers questions, but it cannot move work forward. It does not retrieve the right context, trigger the downstream tool, or know when it is wrong.

The gap is not the model. It is the system around it: retrieval, tool access, control flow, and the guardrails that decide when a human steps in.

## We architect the system around the model
We design agents as bounded systems with explicit state, tool contracts, and confidence thresholds, not open-ended prompt chains. Each agent knows what it can touch, what 'done' looks like, and when to escalate.

For complex work we compose multiple specialized agents behind an orchestration layer, so responsibilities stay legible and failures stay contained.

## What we build
- **Task-running agents**: Single-purpose agents that complete a defined job end to end: retrieve, reason, act, verify.
- **Multi-agent systems**: Specialized agents coordinated by an orchestrator, with clear hand-offs and shared context.
- **Tool & data integration**: Typed tool contracts wiring agents into your real APIs, databases, and internal apps.
- **Guardrails & human-in-the-loop**: Confidence scoring, approval gates, and audit trails so autonomy never outruns oversight.

## Stack
- **Agent frameworks:** Claude Agent SDK, OpenAI SDK, Gemini SDK, LangGraph
- **Orchestration:** Tool calling, State machines, Queues, Event-driven flows
- **Runtime:** Node.js, Python, Vercel, AWS

## FAQ
**What is agentic development?**

Building software where an AI agent, not a fixed script, decides the next step: it retrieves context, reasons over it, calls tools, and checks its own work, with humans gating the high-stakes moves.

**Do you build custom AI agents?**

Yes, custom AI agents and multi-agent systems, from a single task-running agent to a coordinated operating system, wired into your real tools and data.

**How is an AI agent different from a chatbot?**

A chatbot answers questions inside a conversation. An agent takes action: it pulls the right context, triggers downstream tools, and works toward a defined outcome, escalating to a human when it is unsure.

**Which models and frameworks do you use?**

We are model-agnostic, typically Claude, OpenAI, or Gemini behind a typed tool layer, and choose the framework per task rather than forcing one stack.

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Canonical page: https://www.sentientarc.com/capabilities/ai-agents