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Agentic AI systems
Design, build, trace and secure AI agents that take real actions — so they are reliable enough to trust with your workflows and safe enough to connect to your systems.
An AI agent is more than a chatbot: it plans, calls tools, reads documents and changes things in other systems. That makes it powerful, and it makes failures expensive — a wrong step, a runaway loop or a malicious instruction hidden in a document can have real consequences. MatnikAI treats agents as production software: designed for a clear job, observable end to end, measured against verifiable tasks, and locked down by default.
Workflow design
- Choosing where an agent adds value — and where a simple, deterministic workflow is the better answer.
- Task decomposition, tool and API design, and multi-agent orchestration.
- Human-in-the-loop checkpoints for approvals, escalation and irreversible actions.
Implementation
- Agents built on modern LLM tool-use, with typed tool interfaces and integrations (including MCP servers) to your data and systems.
- Robust control flow: retries, timeouts, budgets and graceful failure instead of silent errors.
- Evaluation harnesses with verifiable tasks, so you know how often the agent actually succeeds before it goes live.
Tracing & observability
- End-to-end traces of every model call, tool call and decision, so any run can be replayed and explained.
- Cost, latency and success-rate monitoring, with alerts on drift and regressions.
- Audit trails suitable for review by security, compliance or customers.
Agent security
- Defense against prompt injection and data exfiltration through documents, web pages and tool results.
- Least-privilege tool permissions, sandboxed execution and careful handling of credentials and secrets.
- Red-teaming and security review of existing agents, frameworks and vendor integrations.