Service
AI Agents
Autonomous software that processes invoices, triages tickets, and qualifies leads. Your rules, human oversight when it counts.
Overview
Autonomous agents take over repetitive, high-volume workflows your team handles today. Each one operates within a structured state machine with defined steps, decision points, and human approval gates on high-stakes actions. A single agent might query your ERP, draft a purchase order, and route it for sign-off. A multi-agent system might have a researcher gathering data, an analyst summarizing findings, and a coordinator pushing actions into your CRM. Runs are logged, auditable, and resumable across sessions.
Capabilities
State Machine Architecture
Each agent follows a directed graph of steps with explicit inputs, outputs, and branching conditions. This means predictable behavior you can audit, not a black box that surprises you in production.
Tool Use & Function Calling
Agents interact with your existing systems: they query databases, call APIs, generate documents, and update records. Typed schemas and retry logic ensure reliable execution across OpenAI, Anthropic, and open-source models.
Human-in-the-Loop
For actions above a defined threshold, the agent pauses, presents its reasoning and proposed action, and waits for human approval before proceeding. You decide where the guardrails go.
Memory & Persistence
Agents remember context within a session and across sessions. Short-term conversation memory, long-term vector retrieval, and structured state in PostgreSQL mean an agent picks up exactly where it left off.
Deliverables
- Deployed agent API with defined state machine and tool schemas
- Admin dashboard for monitoring runs and intervening
- Test suite covering happy paths, edge cases, and failure modes
Tech Stack
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