AI Gateway
A single layer under every AI app you run.
Acme AI Gateway routes each AI app through one managed layer, giving teams 30+ hosted and open-weight models, shared company context for sharper answers, and the guardrails and audit trail needed for a company-wide rollout.
Shared rules for models and tools
Teams adopt new AI apps faster than policies can follow. The gateway puts model calls and MCP tool use behind the same set of rules, whichever app a request starts from.
Protection on every call
Each model request, MCP call and skill passes through checks for prompt injection, with optional filters for topics your company has ruled out (beta).
Context travels with the request
Requests pick up facts from the Acme Enterprise Graph on the way through, so every AI app knows how your systems, files, teams and processes relate to each other.
AI observability
Follow the spend, call by call.
Usage reports split traffic by model, person and app, showing what each costs, which MCP tools and servers get called, and which teams lean on them most.
Model hub
Spend fewer tokens by choosing models well.
Pick from 30+ hosted and open-weight models behind one managed layer, so you can swap providers freely, trim token use, and try new releases the week they ship.
Enterprise Graph
Sharper context for every AI app.
Acme turns company data into a graph of how teams, projects and systems relate, and hands that map to each AI app so its answers start from the right facts.
In side-by-side reviews by internal testers, Acme answers won seven of every ten matchups while using about half the tokens.
Inside the AI Gateway
Plug in 30+ models, 120+ connectors, company context, memory and MCP skills behind one managed layer (skills arriving later).
Screen model and MCP traffic for injected instructions, block unsafe model output, and keep conversations away from off-limits subjects (beta).
Push approved models and tools to every AI app at once through your device management system, without configuring each app.
Watch AI the way you watch servers: request counts, response times and failures per model, along with token and tool use per person and app.