Stop renting the engine under your product.
If you're building on AI, every request is a cost, a bet on uptime, and data on someone else's servers. ModelBeat routes between your product and those providers so you stop carrying dependencies you never chose.
In beta. Five models live today, OpenAI-compatible, non-streaming.
You own the product. Somebody else owns the part that thinks.
Every AI company is now building an application layer on top of computation it does not control. That is three problems at once: your margin is set by a supplier, your uptime is set by a supplier, and your customers' data sits on a supplier's hardware.
Your gross margin is theirs to set
Most requests do not need a frontier model, but they are billed as though they do. A price change on their side is a margin cut on yours, with no notice.
One outage away from downtime
A single hard-wired provider means their rate limit, their incident, and their deprecation notice all become yours.
No answer for the security review
Enterprise buyers ask where the data goes and who saw it. If the honest answer is a third-party API, the deal slows down or stops.
Make ModelBeat the default backend behind your product.
You already know how to build the product. What you should not have to build is a routing layer, a failover layer, a caching layer, a cost ledger, and a compliance story for every model you add. ModelBeat is that layer, and you run it yourself.
Margin you keep
Routing routine work to smaller and open-weight models cuts cost per request without cutting output quality. That difference goes to your gross margin instead of a supplier’s revenue.
No single supplier
Models are candidates, not commitments. If a provider raises prices, changes terms, or goes down, traffic moves. Your product does not need a release to survive it.
An answer that closes deals
Offer your customers a deployment where their data never leaves their environment. Sovereignty stops being an objection you handle and becomes a feature you sell, available to design partners now.
A gateway hands you a menu. An orchestrator makes the decision.
Resellers give you one endpoint and leave the choosing to you, which means you still write the routing logic. ModelBeat does the choosing per request, before inference, not after a failed attempt.
Read the request, then eliminate
A model whose output cap, context window, or capabilities cannot serve the request is excluded before cost is considered.
Cheapest survivor wins
Among models that can actually serve it, cost decides. A code or reasoning hint raises the quality floor.
Tell you what answered
Every response carries routing_info: model, provider, whether a fallback fired, and what it cost.
Privacy is not a setting. It is where the computation happens.
A policy page does not keep data in the country. Running the work on hardware you control does. ModelBeat installs inside your environment, so there is no vendor round trip to trust.
The engine runs where you run it
Installs on your servers, your cloud, or fully offline. Data never leaves your perimeter.
Nothing goes outside unless you allow it
You set the rules for what reaches a frontier API. Everything else is blocked.
Every request is accounted for
Full trace of which model, why, what cost, who asked. Export-ready for any audit.
Open weights keep the option yours
Selected for deployability and licence. Frontier is a choice, not a dependency.
Everything stays inside your perimeter
Thousands of models ship every month. Almost none of them belong in production.
Elytra watches every new release, tests it on real hardware and data, and only promotes models that pass a human review giving you a trusted shortlist, not a catalogue to sift through.
Everything the engine needs to be trusted in production.
Predictive routing
Each piece of work is scored on quality, latency, cost, and residency before inference, not after a failed attempt.
Automatic failover
If a provider degrades, rate-limits, or goes dark, traffic reroutes in real time and your code never notices.
Per-request cost accounting
Every response carries the tokens, the price components, and the total, computed against a versioned price table. Reconciliation is arithmetic, not an estimate.
Governance and guardrails
Per-team budgets, policy enforcement, and immutable audit logs, built against SOC 2, GDPR, the EU AI Act, and ISO/IEC 42001. Certification in progress, not claimed.
Bring your own models
Register a private endpoint or a self-hosted deployment. It is probed and benchmarked before it is routable, the same gate every model in the estate passes. In development.
One line to adopt
Drop-in compatible with the OpenAI API. Point the official OpenAI SDK, in any language, at our base URL and keep every call signature you already have.
Licensed inside your walls, or metered from ours.
Sovereign deployment
The full orchestrator runs in your environment. Neural Arc never sees a prompt, a document, or a response. The optional heartbeat carries metadata only, and you can turn it off. Helium One can sit on top as an optional workspace layer.
- DeploySelf-host, in your cloud account, on-premise, or offline
- PricingAnnual licence with seats or usage
- Built forAI companies selling into regulated buyers, and regulated buyers themselves
One key, every model
Prepaid orchestration through a managed endpoint. A single ModelBeat key can serve every application across your business rather than one key per product.
- DeployManaged cloud, live in under an hour
- PricingPrepaid usage, no card required to start
- Built forProduct teams shipping across multiple models
Put the engine back where it belongs.
We are onboarding teams building AI products who want frontier-grade output without handing their margin and their customers' data to someone else. Tell us where you want your inference to run.
Drop-in for the OpenAI API · self-host or cloud