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The model is commodity. Routing, evaluation, and governance are the work.

Connect your product or internal tools to models from every major provider, routed by task and benchmarked against your own data, governed on every call. CreateOS forward-deployed engineers set it up with you, so your team stops picking models and starts shipping reliable AI.

  • ISO 27001 certified, SOC 2 Type II attested
  • Every major provider, model-agnostic
  • Automatic failover on every call
  • Governed and auditable by default

The gap is production, not the model

Most teams spend engineering time picking models instead of shipping products. The right answer is a routing layer that selects, evaluates, and governs model calls so you never rebuild when a provider changes.

  • 95%

    of organizations report no measurable return from generative AI.

    MIT NANDA survey, 2025

  • $5.56M

    average breach cost in financial services, the exposure ungoverned AI adds.

    IBM, 2025

  • 65%+

    of new cyber-insurance now excludes ungoverned AI risk.

    Munich Re, 2026

What we deliver

A unified model layer built for production: routing, evaluation, cost tracking, and governance from the first call.

  • Unified model API with failoverOne routing layer across every major provider. If a provider returns an error or degrades, the router falls over to the next-best option automatically, with no code change on your side.
  • Task-based model routingDifferent tasks need different models. We configure routing rules so each request goes to the model that performs best on that task class, by latency, cost, and output quality.
  • Custom evaluation and benchmarkingWe build evaluation harnesses against your business metrics, not generic leaderboards. Before a model swap goes live, it is benchmarked on your actual production inputs.
  • Cost tracking and optimizationPer-model, per-request cost tracking with aggregated reporting. We surface which models are running over budget and which tasks can be routed to a cheaper model without a quality drop.
  • Provider swap without rebuildThe routing layer abstracts the provider API. You swap a model, adjust a routing rule, or add a new provider without touching application code or redeploying.
  • Governance and output validationPolicy enforcement and PII masking run on every model response before it reaches a user or downstream system, regardless of which model produced it. Hallucination checks are configured per agent.

How an engagement works: The Production Path

A staged path from concept to governed production. Value lands early and governance holds at every step.

  • 01DiscoverWe map your current model usage, identify the highest-value routing and evaluation gaps, and produce a build spec and production roadmap. Fixed pricing agreed in writing.
  • 02ProveWe stand up a routing layer on the execution layer, benchmark candidate models against your own production data, and prove the cost and quality case before any broader rollout.
  • 03ProductionizeForward-deployed engineers harden it: task-based routing rules, evaluation harnesses, per-model cost tracking, output validation, and a full audit trail.
  • 04ScaleIt goes live, then spreads. Model lifecycle management, ongoing benchmarking, and provider swaps on the governed layer you keep.

Proof: 100+ models behind one governed layer

CreateOS integrated 100+ LLM models into a single routing layer for an AI SaaS platform, with RAG knowledge retrieval, automatic fallback handling, and per-model cost tracking. The platform team went from managing individual provider integrations to a single governed interface that routes, evaluates, and reports on every call. The result was a 60% reduction in model-related operational overhead.

See case studies
  • 100+

    Models reachable through one routing layer, with automatic fallback across providers.

  • 60%

    Reduction in model-related operational overhead after the unified routing layer went live.

  • Per-call

    Cost tracking and per-model reporting across every request, with no manual aggregation.

Integrations we put into production

Common LLM integration patterns we take live on the execution layer, each cited and auditable.

Explore use cases by industry
  • Unified API layer with failoverA single interface across every major provider with automatic failover. When a provider degrades or returns an error, the router switches without application downtime or a code change.
  • Per-task model routingRouting rules that send each request class to the model that performs best on it. Extraction tasks, summarization tasks, and generation tasks each get the model suited to them.
  • Custom benchmarks on business metricsEvaluation harnesses built against your production inputs and your quality criteria, not generic academic benchmarks. Model selection is based on what matters to your product.
  • Cost tracking and model swapsPer-model, per-request cost visibility with aggregated reporting. Provider swaps and routing rule changes go live without a rebuild or redeployment.
  • Evaluation harnesses for ongoing monitoringAutomated evaluation pipelines that run on a schedule or on deployment. When a model update changes output quality, the harness catches it before users do.
  • Provider migration without rebuildThe routing layer abstracts the provider API. Adding a new model or swapping a provider is a configuration change, not an engineering project.
  • Governed output validation on every callPolicy enforcement and PII masking run on every response before it leaves the layer, and hallucination detection is configured per agent. The same governance applies regardless of which model produced the output.
  • RAG integration with model routingRetrieval-augmented generation wired into the routing layer. The retrieval step and the generation model are selected together, benchmarked against your knowledge base.

Why CreateOS for LLM integration

  • Model-agnostic, no lock-inThe routing layer works across all major providers. You are not locked to one model or one API. Swap providers or add models without touching your application code.
  • Benchmarked on your data, not leaderboardsWe evaluate models against your production inputs and your quality criteria. A model that tops a leaderboard may perform poorly on your specific task class.
  • Swap providers without rebuildingThe abstraction layer means model changes are configuration, not engineering. Add a new provider, adjust a routing rule, or swap a model in hours, not sprints.
  • Governed on every callPolicy enforcement, output validation, and a full audit trail are on from the first call. Governance does not degrade when you change models or add providers.

Common questions

Which models does CreateOS support?

Through the CreateOS router we route across models from every major provider. The routing layer is model-agnostic, so adding a new provider or model is a configuration change, not a rebuild.

What does 'every major provider' mean in practice?

It means your application sends one request to the routing layer, and the router selects the provider and model based on your configured rules: task class, cost budget, latency target, and fallback order. You are not calling each provider's API. You are calling one.

What does this engagement cost?

Engagements run on fixed-scope pricing, not hourly retainers. A discovery sprint and routing layer design is agreed in writing before any build begins. Cost depends on the number of models, integration depth, and evaluation requirements.

How long does it take to go live?

A routing layer for an existing product typically goes live in four to eight weeks. Engagements that include custom evaluation harnesses and per-model cost tracking run eight to twelve weeks. A discovery sprint produces the exact scope and timeline before build begins.

How do you benchmark and evaluate models?

We build evaluation harnesses against your production inputs and your business quality criteria. Candidate models run against the same inputs and are scored on the metrics that matter to your product: output accuracy, latency, cost, and task completion rate. A model swap does not go live until it passes the benchmark.

Who owns the IP after the engagement?

All code, routing configuration, evaluation harnesses, and IP are yours outright. We document everything and train your internal team to manage and extend what has been built.

Where does our data live and how is it protected?

In your environment. CreateOS runs in your VPC or on-premise, with region-locked compute and zero data retention by default. Model calls are routed through the governed layer, and every call is logged with a full audit trail. Regulated data never crosses a boundary you did not approve.

Where do you want to start?

Bring your current model integration. We will benchmark it, build the routing layer, and put it under governance.