01
LLM
The machineGenerates, reasons, explains, and creates with model routing and provider choice.
Route tasks to the right model by quality, latency, privacy, and cost constraints.
Platform · Public preview
A reference operating model for governed AI production.
Compose models and infrastructure while maintaining one operating model for quality, security, cost, approvals, and accountability. The current public experience presents the architecture and a deterministic simulation; live platform capabilities are being built in stages.
02
RAG
Raw material roomFinds grounded information before the model works.
Ingest, chunk, rank, cite, and refresh enterprise knowledge with source-aware retrieval.
03
Vector DB
Storage warehouseStores knowledge in vector form and retrieves by meaning.
Use hybrid semantic and lexical retrieval with tenant isolation and lifecycle controls.
04
AI Agent
Floor managerPlans work, selects tools, and completes multi-step tasks.
Run auditable plans with approvals, retries, budgets, memory, and human escalation.
05
MCP
Power outlet standardConnects agents to tools, apps, APIs, files, and databases.
Expose governed capabilities through standardized tool discovery and invocation.
06
Guardrails
Safety systemDefines what AI should and should not do.
Apply policy checks to prompts, retrieved data, tool calls, outputs, and sensitive actions.
07
Evals
Quality checkTests correctness, safety, usefulness, cost, and latency.
Continuously compare versions, detect regressions, and gate releases with measurable evidence.
Platform principles
Designed for change without operational chaos
Provider neutral
Switch models, retrieval stores, and tool backends without redesigning the user experience.
Composable by layer
Adopt the full operating model or integrate one capability at a time into an existing environment.
Governance modeled first
Represent budgets, policies, approvals, and evaluations as first-class run configuration.
See how the layers cooperate in an illustrative production run.
Open factory simulation