Know what each model is good at.
Canonical identities, comparable capabilities, constraints, and provenance-backed evidence.
The control plane for
adaptive intelligence.
MC-1 sits above models and infrastructure, turning every task, policy, budget, privacy boundary, and performance objective into a governed execution decision.
INTELLIGENCE LIFECYCLEOne request.
One request.
Seven control points.
MC-1 evaluates authorization before optimization, selects only eligible routes, and records the evidence needed to explain each decision.
- 01Understand
- 02Authorize
- 03Budget
- 04Select
- 05Execute
- 06Evaluate
- 07Improve
SYSTEM CAPABILITIESMore than
More than
model routing.
Routing is one decision inside a broader control loop for quality, security, economics, and adaptation.
Choose where it should run.
Cost, latency, health, quota, region, privacy, and availability shape provider eligibility.
Authorize before execution.
Identity, permissions, policy, and risk gates constrain sensitive tools and actions.
Verify the outcome.
Deterministic and model-assisted checks support bounded recovery and escalation.
Control intelligence economics.
Budgets and objectives guide every route without obscuring underlying inference cost.
Learn when routing is not enough.
Measured demand can inform experiments and customer-controlled specialization.
PROVIDERS · BYOK · PRIVATE COMPUTEYour infrastructure.
Your infrastructure.
One execution plane.
MC-1 can evaluate approved customer compute, direct providers, managed routing networks, and private infrastructure without treating them as interchangeable.
Keep your contracts and keys.
Customer compute is preferred when eligible, and its provider cost remains outside MC-1 managed inference billing.
Route across approved capacity.
Nebius, Together, Fireworks, NIM, and network routes require valid credentials, health, pricing, and policy eligibility.
Keep execution inside the boundary.
Local-only, private, region, and restricted-data declarations prevent ineligible managed egress.
EVIDENCE · RESEARCHMeasure intelligence
Measure intelligence
as a system.
MC-1 separates controlled measurements, cited third-party evidence, and explicit projections. Empty evidence remains empty instead of becoming a marketing number.
Controlled MC-1 evaluations
Quality, cost, latency, tool behavior, and completion evidence appear only after a benchmark is recorded.
Cited external results
External evidence retains its source and is never presented as an MC-1-controlled measurement.
A Mixture-of-Models Intelligence System
Kouadio and Li describe the architecture, formulation, evaluation method, and research agenda.
Read the preprint →COMMON QUESTIONSMC-1 is a control plane,
MC-1 is a control plane,
not another foundation model.
It operates above independently trained models and separates the decision layer from the infrastructure that performs inference.
Filter, rank, execute, evaluate.
MC-1 extracts request features, applies tenant policy, ranks eligible model-provider pairs, then executes and evaluates within explicit limits.
The execution plane is open.
Customers and providers can supply compute. ColomboAI does not need to own the underlying infrastructure.
Open a project and send a request.
The console exposes route, usage, policy, and operational details through one production surface.
OPEN EXECUTION PLANE
Explore enterprise controls ↗Your models. Your keys. Your compute.
Use managed providers, BYOK, private infrastructure, or eligible local execution without coupling application logic to one model vendor.