Move beyond rigid prompt chaining. We engineer collaborative, self-healing multi-agent networks that plan, execute, and verify complex enterprise workflows with deterministic guardrails.
Supervisor-worker agent topologies using LangGraph with structured state graphs, loop-prevention heuristics, and deterministic handoffs.
Equipping LLM agents with typed Model Context Protocol (MCP) bridges into Cloud SQL, ERPs, CRMs, and internal enterprise microservices.
Evaluator and critic agents that run unit tests and cross-examine outputs before downstream execution or transactional commit.
Persistent episodic memory combining Redis vector cache with transactional PostgreSQL state stores for multi-day workflow continuity.
Automated risk-tier interception routing high-value transactions or edge cases to executive sign-off interfaces.
Private on-premises and dedicated VPC deployment using open-weights models (DeepSeek-R1, Llama 3.3) with 100% PDPA compliance.
Deconstruct complex operations into directed acyclic state graphs with explicit tool boundaries.
Develop type-safe RPC and REST connectors with schema validation and mock sandboxes.
Implement ReAct / Plan-and-Solve patterns with calibrated critique prompts and evaluator loops.
Automated fuzz testing to eliminate hallucination leaks, infinite loops, and token budget drains.
Deploy into enterprise VPCs with SAML/SSO authentication, role-based HITL, and data egress audits.
Live Langfuse telemetry tracking task completion rates, token costs, and fine-tuning worker agents.
Start with our 5-day AI & System Review or commission a tailored 6-week agentic MVP sprint.
