AI Agents
AI Agent Development
Agents that take real actions in your systems — grounded on your data, bounded by guardrails, and measured by evaluation, not demos.
What We Do
What goes into a production agent
Agent Design
Task decomposition, planning, memory, and the right level of autonomy for each workflow — from single-step assistants to supervised multi-step agents.
Tool Use & Integrations
Secure connections to ticketing, ERP, CRM, databases, and internal APIs, including MCP servers, with least-privilege access.
Retrieval & Knowledge
RAG over your documents, manuals, and records, with citations so answers can be checked against the source.
Multi-Agent Orchestration
Specialist agents coordinated by a supervisor, with clear hand-offs, retries, and cost and latency budgets.
Guardrails & Human Oversight
Approval steps for risky actions, PII redaction, prompt-injection defenses, and audit trails for every decision.
Evaluation & Observability
Test suites on real tasks, regression checks on every change, and tracing of cost, latency, and failure modes in production.
Platforms & tools our engineers work in daily
FAQ
Common questions
- What is an AI agent, and how is it different from a chatbot?
- A chatbot answers questions. An agent decides on steps, calls tools and systems of record (ticketing, ERP, databases, APIs), and completes a task, with checkpoints where a person approves risky actions.
- How do you keep agents from making costly mistakes?
- Scoped permissions, human-in-the-loop approvals for irreversible actions, an evaluation suite that runs on every change, and audit logs for every tool call. We set the autonomy level with you, then raise it as the evidence supports it.
- Which models and frameworks do you use?
- We are model-agnostic. We work with Claude, OpenAI, and open-weight models, via direct APIs or AWS Bedrock, and use frameworks such as LangGraph only where they earn their place. The right choice depends on your data, latency, cost, and compliance constraints.
- How do we start?
- With a fixed-scope pilot of two to six weeks on one workflow, with success criteria agreed up front, so you can judge the results before committing to a larger program.
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