Agentic AI Systems

Design and deploy agent swarms with safety rails: supervisor-worker patterns, tool-calling, and deterministic fallbacks. Each graph ships with tracing, evals, and governance checks so pilots can graduate to production without rewrites.

• Supervisor-worker agents with guardrails and human-in-the-loop overrides
• Observable, testable agent graphs (LangGraph) with evals and benchmarks
• Cost/latency optimization via batching, streaming, and caching
• Risk controls: auth, PII handling, circuit breakers, and escalation paths

Expected outcomes

• Cut manual review cycles 70–90% in legal/operations workflows
• Shorten decision time with autonomous research/summarization agents
• Improve reliability with continuous evaluation and rollback patterns

Reference stack