CEO & Co-Founder
Paul cofounded Blits.ai and runs the business. He comes from enterprise sales and knows what it takes to get AI working inside a big company.
Paul looks after the business side of Blits.ai. He worked in management consulting and enterprise sales before this, so he knows what large organizations need before AI can work for them.
As CEO he built the relationships with our major clients, raised the funding and pushed to get Blits.ai seen as a leader in enterprise conversational AI. He's good at explaining complicated tech in terms of what it's worth to the business, and that has had a lot to do with how Blits.ai grew.
"It's not the best technology that sets you apart, that's hygiene. What matters is knowing how to apply AI effectively in an enterprise environment."
Paul teamed up with Len in 2018. Len had the technical depth and Paul had the business sense. He'd worked in business strategy, had a good nose for market opportunities, and saw the same potential Len did.
From there it was late nights and one experiment after another, building the base of what became Blits.ai. They believed in it, stubbornly, and they were already thinking about where enterprise AI was headed, way beyond a single product.
They aimed high. Put Blits.ai on the international map, and show that conversational AI could be powerful and still practical for large organizations.
"Scaling takes more than extra users or extra models. You have to build a resilient company that can support customers around the world, 24/7." (Paul Coerkamp, CEO & Co-Founder)
Posts on business strategy, enterprise AI and growing a tech company
Models are converging and getting cheaper to swap, so the durable engineering in enterprise AI is moving somewhere else: the layer that decides who may act, what is remembered, when a human takes over and what gets evidenced. A build guide for the part of your AI stack you'll still own in five years.
Len, Coen and I spent two days on our stand at Ai Everything Abu Dhabi and had more than 75 conversations with banks, government entities, telcos, investors and fellow founders. Five themes kept coming back, and together they point one way: from impressive demos to measurable results in production.
Chargebacks are heading for 337 million a year, most of them aren't real fraud, and each one costs a multiple of its face value. A practical look at the six AI jobs hiding in one dispute, what each of them needs to be governed, and why agentic commerce will change the volume.
Our newest product turns a bank's own transaction data into a wellbeing score, plain language insight and gentle nudges toward healthier money habits. It runs inside the bank, it measures its own impact, and it will never give financial advice. Here is how it works.
MOS has saturated and demos are hand tuned. The lab protocol we use to grade TTS on latency, jitter, entity accuracy, barge in and cloning risk.
Start with one agent, and reach for multi agent only for parallel, read heavy work. The case against splitting too early, and how to do it right.
Most MCP breaches needed no exploit code; the servers behaved as specified. What goes wrong in production, and why the new OAuth spec is half a fix.
Most teams treat EU AI Act compliance as a legal side project. A checklist of what enterprises should implement now to avoid disruption and rework.
Blits.ai joins LLMs4EU. Who builds large language models, on what data, and under which European values and regulations, and why that matters now.
Blits.ai now supports GPT-4, bringing new capabilities to chatbot development and deployment. What it means for conversational AI.
Our research into conversational AI performance shows clear gains in chatbot effectiveness across several industries and use cases.
GPT-3 has changed what people expect from conversational AI. Ask it almost anything and you get a fluent, often surprisingly good answer. Whether that makes it practical for a chatbot or voicebot that talks to your customers is a different question, and that is what this article is about.
NLU is often treated as a black box, but knowing how it works is key to building effective conversational AI. A look inside.
