The current economics of enterprise AI are built around tokens and SaaS subscriptions. We're taking a different approach. In his recent conversation with @vladdoes , our CEO @babakph explains why SuperNinja Enterprise is challenging the industry's existing business model. Rather than following the same pricing and delivery structures, we're rethinking how enterprises access and pay for AI. 🔗 Watch the full conversation: youtu.be/R8pCCUPtrj8?si=2iJn…

Enterprise AI should give businesses more control, not less. That was the focus of our breakout session at Agentic AI North America in Reston, Virginia, last week. As a sponsor of the event, we had the opportunity to discuss a different approach to enterprise AI: owning the infrastructure, controlling costs, and keeping ownership of your IP. Thanks to the Agentic AI North America team and everyone who joined us for the conversation!

Most enterprise AI programs aren't small because the models aren't good enough. They are small because the data has to leave the building to reach them. Ninja runs inside your own VPC, or air-gapped. It never leaves.

A lot has changed since our CEO, @babakph, last joined @vladdoes in March. Back then, the conversation was about building AI Employees that could take on complex, long-running work. Now, with the launch of SuperNinja Enterprise, the focus has shifted to making that work economical and practical for enterprises. In their latest interview, they discuss what drove that shift, including conversations with enterprise leaders about unpredictable AI costs and data security concerns. The technology was one challenge. Making it work for enterprises was the next. Watch the full conversation: youtu.be/R8pCCUPtrj8?si=kVwJ…

Every agent demo works until it meets the outdated vendor portal your business runs on. 3,000+ integrations where an API exists. Browser automation where it does not. A process is only as automated as its worst step. ninjatech.ai/enterprise

Tokenmaxxing: when your vendor is paid by how long your agent thinks. Not fraud, just an incentive pointing the wrong way. And a 24/7 agent is your heaviest token consumer. Fixed capacity ends the argument.

What's the cost of your AI agent? @theinformation's @KevKubernetes spoke with our CEO @babakph about how Ninja Enterprise is tackling the “sticker shock” that can come with running agents around the clock. Instead of unpredictable usage-based costs, Ninja gives enterprises a flat-rate approach, with open-weight models at the center and the flexibility to use models from OpenAI and Anthropic when needed. Read the full briefing: theinformation.com/briefings…

What does enterprise AI look like when you own the workforce instead of renting access to it? @Scobleizer took a closer look at SuperNinja Enterprise and the technology behind it. Ninja's AI Employees can work around the clock on long-running jobs, run inside a company's own cloud, on-prem, or air-gapped environment, and use both frontier and open-weight models. It's a different approach to enterprise AI: one built around ownership, flexibility, and finished work rather than seats and sessions. Thank you, Robert, for taking a look under the hood.

SuperNinja Enterprise is here. 🥷 Today, we're launching an #AI workforce built for enterprises ready to move beyond pilots. SuperNinja Enterprise brings AI Employees, GPU capacity, and inference infrastructure together under one contract and a fixed annual bill. It runs in the customer's cloud, with unmetered capacity for open-weight models and the flexibility to use the right model for each workflow. AI Employees can work around the clock on long-running jobs while enterprise teams keep control of their data, infrastructure, and costs. One platform. One contract. An AI workforce ready to get to work. Learn more: ninjatech.ai/news/superninja…

This is what a NinjaTech AI Employee looks like in action. Ninja keeps a job running beyond a single session, building on its work and becoming more specialized as it goes. The work keeps moving until the job is finished. 👇

Token prices keep hitting record lows. Enterprise AI bills keep climbing. Agents burn orders of magnitude more tokens than chat did. Cheaper tokens, bigger invoice. Our estimate: unmetered on open-weight models runs more than 10x cheaper for 24/7 work. ninjatech.ai/enterprise

Enterprise AI pilots rarely fail on capability. They stall because the meter decides who can use them. Unmetered on open-weight models means nobody gets told no. ninjatech.ai/enterprise

What happens when you work with Ninja every day for more than a year? You'll get to see just how much it can evolve. Jeff Gunn has been a daily Ninja user for over a year, watching the platform grow and putting SuperNinja to work along the way. His take: “SuperNinja is on another level, doing some great work together!” And that evolution is exactly the point. Ninja is built to keep working, learning, and getting better at the work you give it.

We asked our AI to explain what an AI employee is. It wrote a song, animated it, and cut the film itself. Sound on. Sorry in advance. ninjatech.ai

Enterprise AI shouldn't stop when the session ends. Get a glimpse of Ninja's AI Employee in action.

We're thrilled to announce that NinjaTech AI has been named a Webby Honoree at the 30th Annual Webby Awards! 🏆🥷 Often called "the Internet's highest honor," the Webbys recognize the best of the web — and being selected among thousands of entries from across the globe is a moment we don't take lightly. This one's for our incredible team, our community, and everyone who believes AI should be smarter, faster, and built for the way people actually work. We're just getting started. 🚀

I asked SuperNinja to build a Product Management training workshop. Manual effort: 1–2 weeks SuperNinja: 15 minutes Here’s what it generated 👇 A complete 2–3 hour PM training module for team leads: 1️⃣ Roadmap Planning Now / Next / Later framework Outcome-based roadmaps Hands-on prioritization exercise 2️⃣ Prioritization RICE Value vs Effort MoSCoW Live scoring workshop 3️⃣ Stakeholder Communication Exec vs Eng vs Sales alignment Structured “No” framework Role-play scenarios 4️⃣ Metrics North Star Metric OKRs Leading vs lagging indicators 5️⃣ Cross-Functional Leadership DACI decision framework Meeting effectiveness checklist Output: 40+ slides Exercises Templates Frameworks Visuals No consultant. No blank PowerPoint. No 2-week build cycle. Research → Structure → Training Module In 15 minutes. This is how internal enablement gets built now. super.myninja.ai #AI #ProductManagement #Leadership #Automation

🚀 Big announcement from @NinjaTechAI: We're launching AI Workforce. Not a chatbot. Not a copilot. A coordinated team of 25+ AI agents that work like remote team. Each one has its own computer, real tools, and a specialized role. They coordinate. They execute. They deliver. Waitlist is open 👇 ninjatech.ai/product/ai-empl… #AIWorkforce #FutureOfWork #superninja

Analyzed 10 top tech newsletters. The formula: • Weekly frequency (daily burns subscribers) • 40% educational, 25% product, 20% stories • Mobile-first design (65% open on phones) • 80/20 rule: value vs promotion Biggest mistake: sending too often. #AI #EmailMarketing #Newsletter #SuperNinja #ContentStrategy

I asked SuperNinja to compare 5 fitness trackers. Manual research: 6–8 hours SuperNinja: 5 minutes Devices analyzed: • Apple Watch • Samsung Galaxy Watch • Fitbit Charge 6 • Garmin Venu Sq 2 • Oura Ring What it found 👇 Best overall sensors → Apple Watch Best Android option → Galaxy Watch Best battery life → Garmin (8–9 days real world) Best for sleep → Oura Ring Best value → Fitbit Charge 6 It pulled: • Expert reviews • Spec sheets • Real-world battery tests • Subscription details • Feature comparisons Then structured everything into decision-ready tables. No 20 open tabs. No spreadsheet chaos. No 3-hour rabbit hole. Research → Structured → Decided In 5 minutes. This is what AI-powered product research should look like. super.myninja.ai #AI #ProductResearch #Wearables #Automation