BLACKBOX AI
Blackbox AI Technologies Inc. · Coding
BLACKBOX AI is an enterprise inference platform that runs open-weight models as dedicated deployments or routes 300+ models through one encrypted endpoint with zero data retention.
About BLACKBOX AI
What Is BLACKBOX AI
BLACKBOX AI is an enterprise inference platform for teams that run models in production. It does two things: it runs the open-weight model you pick through a dedicated AI deployment, or it routes traffic across a catalog of more than 300 models through one OpenAI-compatible endpoint. The company behind it is Blackbox AI Technologies Inc., based in San Francisco.
As an enterprise AI gateway, the pitch is trust. Prompts are encrypted before they leave your machine and decrypted only where the model runs, so the proxy and the host never hold the key. The gateway enforces zero data retention and no training, and a PII anonymization layer strips identifiers before anything reaches a closed model. For regulated buyers, that stack is the reason they look at Blackbox over a bare model API.
The catches are real. There is no self-serve signup flow on the model catalog beyond account creation: the platform is built around a committed annual contract, so you talk to sales from the start. Metering is per token, not per seat, and unused commitment expires at the end of the billing period. Small hobby projects and pay-as-you-go tinkering fall outside the model this platform is designed for.
Getting Started
- Create an account or contact sales to scope the workload, the controls you need, and the token volume you expect.
- Agree a commit against the published per-token rates, then a forward-deployed engineer configures the account with you.
- Grab an API key, point your client at the endpoint, and send a first chat completion request using the OpenAI-compatible schema.
- Set your routing, caching, and encryption options, and add your own provider accounts if you want to bill through them.
- Watch the commit balance in the dashboard and use spend alerts at 75% and 90% to catch usage before it runs out.
Product Information
A quick look at BLACKBOX AI's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Platform and infrastructure engineers
- Compliance and security teams
- Teams running open weights
Tasks
- Routing across many models
- Cloud coding agents
- Private inference on sensitive data
- Fine-tuning on your own tasks
- Cutting model spend
Scenarios
- A fintech platform routing production traffic
- An internal developer platform
- A research team comparing models
Key features
Encrypted Inference by Default
Prompts are sealed in the client and stay encrypted across the wire, and only the model that runs them ever holds the key. The proxy, the host, and the operator never see readable text, which is the difference between a privacy promise and a technical guarantee. Data at rest can run as ciphertext too, so a stolen disk yields nothing useful.
Zero Data Retention Gateway
The gateway enforces zero data retention and no training on routed traffic, backed by provider terms and per-request flags wherever the provider API supports them. Nothing readable is kept after the answer comes back. For teams that have to prove their data isn't reused, this is the control that survives an audit.
One Endpoint for 300+ Models
The Blackbox Router reaches more than 300 models from over 30 labs through a single OpenAI-compatible endpoint and one bill. Open-weight and closed models sit side by side, so you don't maintain separate SDKs per provider. You can also connect your own OpenAI, Anthropic, or Google accounts and bill usage through those existing relationships.
Dedicated Single-Tenant Deployment
You can run the open-weight model you choose as a dedicated deployment isolated from every other customer, on infrastructure Blackbox operates. It includes data residency, customer-managed keys, and a configuration pass with a forward-deployed engineer. This is the option for teams that won't share a multi-tenant endpoint.
Intelligent Routing and Caching
Smart routing sends each request to the model that fits, with automatic failover when a provider wobbles, and prompt caching reuses work you've already paid for. The company says routing and caching extend a commit by 10 to 20 percent even on closed models. In practice, that turns a flat token budget into more usable capacity.
Cloud Coding Agents API
The Agents API runs cloud coding agents, including isolated sandboxes and multi-agent flows where a Chairman LLM orchestrates the others. Dedicated runners with SSO are available for Enterprise accounts. It turns the platform from a raw inference layer into something that can execute development work on its own.
Fine-Tuning on Your Weights
You can adapt an open-weight model to your own data and tasks, from classifying support tickets to shaping structured outputs in your system's format. Workflows run on your own engine or with a forward-deployed engineer's help. Combined with dedicated deployment, this keeps both the model and the inference engine under your control.
Pros and cons
Pros
- End-to-end encryption and zero data retention are enforced at the gateway, not just promised in a policy, which matters for regulated buyers.
- One OpenAI-compatible endpoint covers 300+ models from 30+ labs, so integration work happens once instead of per provider.
- Dedicated single-tenant deployments let you run open-weight models with your own keys and data residency.
- Routing and prompt caching stretch a committed token budget by 10 to 20 percent, according to the company.
- A forward-deployed engineer configures the account at contract start, and implementation is included at no added cost.
Cons
- There's no self-serve paid tier; you have to talk to sales and sign a committed annual contract to get access.
- Unused commitment expires at the end of the billing period, so a poorly sized commit wastes spend.
- Several trust and deployment features, like dedicated runners and data residency, only unlock on Enterprise, not for smaller buyers.
- The dedicated open-weight audit speeds that Artificial Analysis ranked #1 apply to Blackbox-operated infrastructure, so closed models routed to their providers may behave differently.
Frequently asked questions
BLACKBOX AI is an enterprise platform for running AI models in production. Teams use it to route requests across 300+ models through one endpoint with encryption, or to run a chosen open-weight model as a dedicated, single-tenant deployment.
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