CTO & Co-Founder
Len cofounded Blits.ai and runs the tech side. He's done AI and software engineering for over ten years, and he was hooked on conversational AI back when hardly anyone else cared.
Len has been writing software and working on AI for more than ten years now. He got into conversational AI early, well before it went mainstream.
As CTO he built the Blits.ai platform from scratch, with big company requirements baked in from day one. He knows machine learning, NLU and AI security inside out, and that's a big reason major financial institutions and international corporations were willing to partner with us.
"Building enterprise AI takes more than technical skill. You also have to understand business strategy and customer dynamics."
It started with frustration. In 2018 Len was at a global consulting firm and kept watching large companies pour millions into chatbots, only to be let down. The tech didn't live up to the hype and they got stuck with stiff systems that couldn't bend to what they needed.
Len took something else from it. He'd been tinkering with the IBM Watson API and could see how far conversational AI could go. He had a hunch people would stop clicking around and just talk to their computers, same as they talk to each other.
"We're going to talk to our computers, not just click through menus."
That's where Blits.ai came from. A platform that gives large enterprises the control, flexibility and power to build conversational AI that actually does the job.
Posts on AI, enterprise tech and building conversational AI
Strict data rules, no local AI cloud region, no GPUs, and a board that wants agents live this quarter. For a lot of banks and other regulated organizations that used to mean picking two out of three. Our new privacy shield removes the trade off: the best cloud models do the thinking, and the personal data never leaves your building.
We built a public library of 257 AI use cases and 1,377 real deployments, with every number quoted from its source and labelled with who made the claim. The verdict: AI is doing real work, the industry can't prove it, and the sellers are writing the benchmarks.
The 95 percent pilot failure stat is making the rounds again, this time with a diagnosis I actually agree with: chatbots automate sessions, but a bank runs cases. Why the unit of work decides whether your AI survives production, and the day eight test that shows which one you built.
Our banking use case map grew from 21 to 81 jobs, so we turned it into a playbook. Along the way the story changed: the destination is the AI bank, where the work itself runs on governed AI, and what decides who gets there is governance far more than the models.
Per seat licensing carried software for a decade, but agents don't sit in seats and token pricing breaks the moment AI succeeds. Where AI pricing lands.
Procurement wants us to be a software vendor or an implementation partner. We are neither, and I think the model in between is what gets AI into production.
