Autonomous and semi-autonomous agents designed around business processes, with the guardrails to run unattended.
Overview
An agent is only useful when it can be trusted with a task end to end. We design the tool surface first — what the agent may read, write and trigger — then constrain the loop around it.
Every agent ships with an audit trail, escalation paths to a human, and hard limits on scope. Autonomy is a dial, not a switch.
- Tasks handled unattended
- 82%
- Cost per task reduced
- 58%
- Escalation accuracy
- 96%
Figures are medians across recent engagements in this practice, not best-case results.
- Agent architecture and tool design
- Multi-agent orchestration
- Human-in-the-loop escalation
- Long-running task execution
- Memory and context strategy
- Action auditing and traceability
- Failure recovery and retries
- Agent evaluation and scoring
- 01
Agent specification
Task boundaries, tool contracts, escalation rules and success criteria agreed before a line of code.
- 02
Deployed agent runtime
An observable runtime with queueing, retries, rate limits and a full record of every action taken.
- 03
Operator console
A review surface where your team approves, corrects and learns from what the agent did.
- LangGraph
- Temporal
- Redis
- PostgreSQL
- TypeScript
- Python
Tell us the constraint you are trying to remove. A senior engineer will read it and reply within one business day — no sales sequence.