NinjaTech AI today launched SuperNinja Enterprise, an AI workforce platform that puts AI employees to work around the clock inside the customer’s own cloud, on a fixed annual bill, with the computing capacity delivered under the same contract. It runs open-weight models and keeps enterprise data inside the customer’s boundary.

For the first time, NinjaTech AI is also supplying the GPU and inference capacity the platform runs on. Customers get one product that combines the AI software, model-serving infrastructure and compute, rather than assembling those pieces from separate vendors.

“With SuperNinja Enterprise, your CISO can rest assured data never goes outside your own walls,” said Babak Pahlavan, CEO of NinjaTech AI. “Your CFO gets an AI bill that doesn’t move. And everyone sleeps well, knowing you can scale AI without waking up to skyrocketing costs.”

What Sets SuperNinja Enterprise Apart

  • Lower cost than frontier models: Total cost is about 10x lower, running open-weight models.

  • Turnkey capacity: GPUs, inference and software in one contract, with no infrastructure vendor to assemble first.

  • Unmetered open-weight compute: AI reaches every employee, not stopping at a rationed pilot.

  • AI workforce that enterprises own: AI employee production and outputs remain in the enterprise’s own tenant.

  • Enterprise data is not pooled: It never trains any outside models.

  • Fixed annual pricing: Consistent annual pricing that holds as usage increases.

  • 24/7: AI employees that take a goal and finish the work, running unattended around the clock.

  • Swappable models: The freedom of never being locked into one AI lab.

  • Works in the tools enterprises use: Integration into Slack and Microsoft Teams.

  • Expandable on-demand: Packages sized for 100, 500 or 1,000 AI employees.

Cost and Data Concerns Limit Enterprise AI Adoption

Many enterprise AI initiatives stall for two reasons. Teams cannot forecast usage-based pricing, and they can’t hand their most sensitive work to an outside AI service. A fixed annual bill inside the customer’s own environment answers both.

AI agents have advanced enough to handle long, unattended jobs, but that means they now burn far more tokens than a chat interface ever did. But while token prices are generally falling, enterprise AI bills keep climbing. That has kept most enterprise AI deployments stuck in the pilot stage instead of scaling across organizations to drive stronger results.

Model choice stays open. The platform supports Anthropic and OpenAI alongside open-weight alternatives, so customers can move a workflow to the best model for the job without committing to a single AI lab.

Single-Contract Deployment Model

Deploying enterprise AI today usually means securing GPU capacity, standing up model-serving infrastructure and deploying applications across separate vendors and contracts. The offering combines all three into one.

NinjaTech AI delivers GPU and inference capacity through Microsoft with Fireworks AI or AWS, on single-tenant capacity reserved for the customer. Neither side buys hardware. Organizations that run open-weight models on that reserved capacity see end-to-end costs about 10 times lower than comparable deployments on frontier lab models.

Customers whose most sensitive work cannot touch an external network can instead choose a licensed deployment inside their own air-gapped environment, where they supply the hardware. NinjaTech delivers the dedicated capacity above end-to-end.

Platform and implementation arrive in one contract at one price. Healthcare customers work with NinjaTech AI integration specialist Optimum HealthcareIT, and other enterprises work with Infosys.

SuperNinja Enterprise is available now. Enterprises can start with a fixed-scope pilot that puts AI employees on real work in days, then expand into an annual capacity contract.

“Most vendors keep AI on a usage meter,” Pahlavan said. “We give enterprises predictable capacity and costs, so adoption can spread across the organization instead of stopping at a pilot.”

Additional Resources

About NinjaTech AI

NinjaTech AI builds the AI workforce. Ninja is a platform for general-purpose, self-evolving AI employees that are hired, onboarded, and specialized the way staff are. They work 24/7 on long-running jobs across the apps a company already uses, collaborate with people in Slack and Microsoft Teams, and run on the best frontier and open-weight models. Ninja deploys as a managed service or, on open-weight models, licensed into a customer’s own cloud, data center, or air-gapped environment with unmetered inference on hardware the customer owns. It offers unlimited seats and SOC 2 Type 2 compliance. The company was founded in 2022 and is based in Palo Alto, California. To learn more, visit www.ninjatech.ai and follow us on LinkedIn.

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