MCI Co-Build
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The AI agent platform for teamsshipping real products.

Most teams stall between a promising prompt and a product customers can rely on. MCI Co-Build closes that gap: specification, architecture, build, evaluation, deployment and day-2 operations for AI agents — in one workspace, on the models and infrastructure you already pay for.

  • No vendor lock-in
  • Model-agnostic
  • Evaluation built in
  • Cost + usage visible
  • Deploy in one click
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Run the six steps live.

Type your product idea and execute any step against the live model right now. Each step shows the real response, real elapsed time and real token usage.

Live model connected.
1

Idea

Turn one line into a product specification.

2

Architect

Model, data, agent, API and deployment layers.

3

Build

The concrete tasks and stack to implement.

4

Evaluate

Quality criteria and red-team checks.

5

Deploy

Environments, release steps and secrets.

6

Operate

Metrics, alerts and running cost.

Why teams choose an operating layer.

Most AI work stalls between the prototype and production. MCI Co-Build closes that gap with structure — for professionals, founders, developers, product teams and enterprises.

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One layer, not ten tools

Specification, architecture, build, evaluation, deployment and operations live in a single workspace with one source of truth.

Secure by construction

Credentials stay server-side, access is scoped per workspace and project, and every change is recorded in an audit trail.

Cost visible before launch

Estimated running cost and production readiness are shown before you deploy, not after the invoice.

Built for teams

Owners, members, reviewers and viewers work on the same product with clear roles and review gates.

We don't replace the AI ecosystem. We orchestrate it.

MCI Co-Build is the control and workflow layer above the models, data and tools you already use.

MCI Co-Build
Control / Workflow
Models
  • OpenAI
  • Claude
  • Gemini
  • NVIDIA
Data
  • Supabase
  • Postgres
  • Pinecone
  • Vector DB
Tools
  • APIs
  • n8n
  • Webhooks
  • MCP
Deployment — Vercel · Railway · Modal
Production Product
Monitor / Optimize

Six steps from idea to operating product.

STEP 1

Idea

Capture the product, its users and the business outcome in plain language.

STEP 2

Architect

Get a recommended model, data, agent, API and deployment design you can adjust.

STEP 3

Build

Generate the working product surface — prompts, tools, data flows and endpoints.

STEP 4

Evaluate

Score quality, task success, security posture and estimated running cost before launch.

STEP 5

Deploy

Ship to a managed environment with preview and production releases.

STEP 6

Operate

Watch requests, uptime, usage, cost and alerts in one operations view.

Ship your first AI product this quarter.

Private beta invites go out in small batches. Tell us what you want to build and we’ll prioritise access accordingly.

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