NinjaTech AI provides an AI employee platform, with its core product named SuperNinja, positioned as an autonomous AI employee that can work 24/7. It is not just a chatbot or editor assistant, but an agent designed to complete real work end to end: after the user gives a goal, it plans on its own, calls tools, checks its own work, and delivers the final result, making it suitable for repeatable, multi-step business processes.
[Main capabilities] SuperNinja is described as having its own computer, able to run on dedicated cloud machines, with an intelligent unlimited context window, able to save progress, self-correct, and continue tasks after restarts, with runtimes lasting from hours to days, weeks, or even months. It can connect to more than 3,000 tools that teams already use, including Salesforce, HubSpot, GitHub, Jira, Notion, Gmail, Stripe, Linear, Figma, and others, through a one-click authorization process, which the company says requires no middleware maintenance, no CSV exports, and no tab switching. The agent can query these tools, write data back, and orchestrate workflows across tools. The platform supports a model-agnostic strategy: each agent can choose frontier large models such as Claude, GPT, and Gemini or open-weight models, and can switch at any time as the market changes, and also supports bring-your-own-model keys and contracts (BYOK). The company says it upgrades to the latest and strongest available models as new models are released. In terms of functional applications, SuperNinja can take on repetitive, multi-step work in finance and accounting, customer support, software engineering, HR and recruiting, operations and administration, legal and compliance, and research and executive support. It can also write, debug, and refactor code, draft and polish content, search and synthesize sources, conduct in-depth analysis and planning, analyze documents, data, and media, and provide templates and prompt optimization, performance and comparison, and other features.
[How to use] SuperNinja runs in the team's existing work environment, and the company describes it as requiring no new app to learn: users can assign work in messages in Slack, Teams, and WhatsApp, observe its execution in conversation threads, and guide it like any other colleague. It is described as "autonomous but not unsupervised": high-risk operations require user approval, and users can view every step and maintain full visibility. The platform can be "onboarded" and trained like a new employee, becoming more closely aligned with the specific business with use; users can delegate tasks and scale them.
[Applicable scenarios] Suitable for those who want to hand off cross-functional, multi-step, repetitive tasks to AI-automated enterprises and teams, for example in scenarios such as financial reconciliation, customer support ticket handling, code delivery, recruitment processes, operations administration, legal compliance, and research support, take over the entire job, not just a single step.
[Deployment and Pricing] NinjaTech AI offers three deployment methods: fully managed SaaS, ready to use out of the box; deployed within the user's own AWS, Azure, or GCP account, VPC, or data center (including air-gapped options); or a hybrid model with bring your own key. The official statement says data will not leave the user's boundary and will not be used to train any model. Regarding pricing, the official statement explains that you can start for free and scale by credits as AI employees take on more work; enterprise deployments run without limits on dedicated GPUs and use a fixed subscription. For deployed versions, the platform runs on GPUs controlled by the user and is paid by GPU hour, rather than by token, task, or seat, and can run an unlimited number of users and parallel agents, with costs capped by hardware. The official statement says that under the same workload it is 5-10 times cheaper than token-billed frontier APIs, and that this spend can count toward Azure MACC, AWS EDP, or Google Cloud CUD commitments. The enterprise edition claims unlimited tokens, a fixed subscription, and about 10 times cost savings. Specific price amounts, free quotas, and subscription tiers are not yet provided.
[Security and Compliance] Each AI employee runs in an independent secure dedicated virtual machine, isolated by agent and thread; data is encrypted in transit and at rest; SSO and full audit trails are standard configuration; SOC 2 Type II review is in progress; the official statement declares that user data will not be used to train any model.
[Limitations and Not Yet Provided] The current materials do not provide specific pricing figures, free quota limits, detailed feature lists for each function, supported interface languages, available regions, service level agreements (SLA), the completion time for SOC 2 certification, or details such as integration limits or permission models for specific tools. This information is not yet provided.
