Sathus AI 2.0 is now generally available — evaluation harnesses and guardrails included. Explore
Deploy stateful multi-agent swarms that autonomously solve multi-step tasks across enterprise software. Built-in evaluation harnesses, real-time safety guardrails, and audit trails.
Common obstacles that prevent enterprises from realizing the full value of AI initiatives.
Unmonitored agents get stuck in recursive execution cycles or generate invalid tool parameters.
Core capabilities that enable production-grade AI systems with enterprise governance.
Coordinate specialized subagents (researcher, planner, execution, reviewer) with shared state.
Run code execution, SQL queries, and API calls inside isolated Docker containers.
Planner agent, tool registry, evaluation harness, Redis memory store, and human approval queue.
The tools and platforms we use to deliver production-grade AI systems.
Agent engineering stages.
Break enterprise workflows into discrete agent roles.
Build benchmark datasets for accuracy, latency, and tool precision.
Deploy agents with human-in-the-loop fallback approval queues.
Measurable results that drive enterprise value from AI initiatives.
Reduction in manual document processing and compliance checks.
85%
Real-world examples of how we've delivered AI solutions for enterprise clients.
MetroBank Corp • Financial Services • 6 Months
Manual verification of complex commercial credit applications took 14 days.
Sathus AI multi-agent swarm analyzing tax forms, credit records, and compliance rules.
Audit time reduced from 14 days to 45 minutes with 100% auditable reasoning chains.
Common questions about our AI Engineering practice and approach.
We implement sandboxed execution environments, strict OAuth2 scope limits, and mandatory human-in-the-loop (HITL) approval steps for state-changing operations.
Let's discuss how our engineering practices can accelerate your business outcomes.
