AI Agent Infrastructure for production-grade agents.
Agents fail in production for the same reasons services do: no routing, no memory, no observability, no rollback. stackcontrolai gives every agent first-class routing, MCP integrations, short- and long-term memory, and pipelines — all governed by the same policy plane as the rest of your stack.
- SOC 2 Type II
- ISO 27001 ready
- EU AI Act aligned
- SaaS · VPC · self-host
Every agent re-invents routing, retries, and memory — badly.
MCP servers run as one-off processes with no health, auth, or audit.
When an agent loops at 2am, nobody can replay the run.
What ships with AI Agent Infrastructure.
Agent registry
Versioned agents with system prompts, attached tools, and memory bindings.
Workflow routing
Intent → agent rules with fallbacks and per-route SLOs.
Memory systems
Redis short-term + pgvector long-term with hit-rate metrics.
MCP integrations
Registered MCP servers with health monitoring, auth, and audit.
Automation pipelines
Step-based execution with retries, branching, and human-in-the-loop.
Replay + traces
Every agent run captured end-to-end; replay against any model.
What counts as AI agent infrastructure?expand
Anything an agent needs that a single LLM call does not: routing across models, short- and long-term memory, tool integrations (often via MCP), step orchestration, retries, observability, and governance. stackcontrolai ships all of it under one control plane.
Do you support the Model Context Protocol (MCP)?expand
Yes. MCP servers are first-class. Register a server, attach it to one or more agents, and the control plane handles health checks, auth, audit, and per-tool RBAC.
How do you handle agent memory?expand
Short-term memory runs in Redis with TTL and per-agent scoping. Long-term semantic memory runs in pgvector with embedding pipelines and cited recall. Hit rates and cost are visible per agent.
Can a non-engineer build a pipeline?expand
Yes. Pipelines are step-based and visual — triggers, agent calls, tool calls, approvals, and outputs. Platform teams own the building blocks; product teams compose them.
Run ai agent infrastructure in your stack.
One control plane your security, finance, and platform teams already trust. Live console, no signup.