AI moves too fast to build on one model
New state-of-the-art image and video models ship every week. So every team burns the same effort: pick a model, wire its SDK, babysit its parameters, watch it fall behind, migrate — and eat the outages and surprise bills in between. Orchestration is the way out: one API above the whole model landscape, where the choosing, tuning, and failure-handling is the router's job. Forever.
Model churn
What's best this month is stale the next. Without orchestration, you re-integrate, forever.
Integration tax
A separate SDK, parameters, and quirks per provider — multiplied across image, video, and everything after.
Failures & cost
Providers rate-limit and go down mid-request; pricing is opaque. Someone has to absorb that. It shouldn't be your product.
One call in. One result out.
Profile
The router reads the prompt — subject, faces, text, complexity, intent.
Score
It ranks every live model on quality-for-goal and price, using current data, not last month's leaderboard.
Route
The request goes to the best model available at this moment.
Reroute
A provider slips mid-request? The router re-picks in milliseconds. The failed attempt costs you $0.
Deliver
One clean result, with the tier and exact cost on the receipt.
The models underneath keep changing, week to week, as new ones climb the leaderboards. That's the design. Your integration is with the conductor, not the instruments, so every model upgrade lands in your product with zero code changes. Pricing stays simple: images from $0.02, video from $0.044 per second of output, with the exact charge on every response and failed generations never billed.
Media is the first movement
Today the orchestration layer conducts image and video generation — one endpoint, six tiers, pay-per-result, and an MCP server so AI agents can call it in plain language with a spend ceiling. But the problem it solves — too many models, changing too fast, failing too often — is the shape of all AI compute. The same routing brain is built to extend across it: everything orchestrated, all the time.
Common questions
What is an AI model orchestration layer?
It's the layer that sits above the model landscape and does the choosing for you. Instead of integrating a specific image or video model — and re-integrating when a better one ships — you integrate once with the orchestration layer. It reads each prompt, selects the best model for that goal at that moment, handles provider failures by rerouting automatically, and returns one result with the exact cost. The models underneath change constantly; your code doesn't.
What is the best AI image or video generation API?
The honest answer: it changes every few weeks. New state-of-the-art image and video models ship constantly, and the best model for a photoreal portrait is rarely the best one for a logo, an anime frame, or a 30-second product video. That's the reason orchestration exists — rather than betting your product on one model, a router re-answers the question on every single request, using live quality and price data.
Do I need to pick a model to use Corent?
No — that's the point. You describe what you want and optionally state a goal: fast, cheap, balanced, or quality. The router picks the model, sets its parameters, and returns the result with the tier and exact charge on the receipt. You never manage provider accounts, SDKs, or model versions.
What happens when a model provider goes down?
Model providers rate-limit and fail mid-request more often than any status page admits. When that happens, the router re-picks the next capable model in milliseconds and completes your request. Failed attempts are never billed — your balance is only debited after a successful result.
Can AI agents use the orchestration layer?
Yes — it's built for them. Corent ships an official MCP server (corent-mcp on npm), so agents like Claude can generate images and video in plain language. Agent calls can carry a max-cost ceiling, so an autonomous agent can create media without ever overspending its budget.
How is Corent different from OpenRouter?
OpenRouter sells access; Corent sells outcomes. OpenRouter is a catalog — hundreds of models behind one account, including images and video — but you still choose the model on every request (it's a required parameter), tune it, and handle it when it fails. Corent deletes that job: you state a goal — fast, cheap, balanced, quality — and the router picks the model per prompt, reroutes in milliseconds when a provider fails, never bills a failed generation, and returns the tier and exact cost on the receipt. If you want to manage models, OpenRouter is excellent. If you want to never think about a model again, that's the product Corent is.
Does orchestration only apply to images and video?
Media generation is where Corent's orchestration is live today: one endpoint for image and video, six tiers, pay-per-result. It's the first movement, not the whole score — the same routing brain is built to extend across AI compute.
Never pick a model again
One prompt in, best result out, exact cost on the receipt. Start with $5 in prepaid credits.
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