Awais Tahseen

I'm a machine learning engineer, not a bookkeeper. But like a lot of people who build things, I found the problem before I went looking for it.
A few months ago I was going through bookkeeping forums and Reddit threads r/bookkeeping, r/freelance, accounting communities doing research on pain points in professional services workflows. I kept seeing the same complaint surface over and over, from solo bookkeepers and growing practices alike. Not about the bookkeeping itself. About the ten days before the bookkeeping could even start.
Bookkeepers were spending the first week or two of every month just trying to get documents from clients. Sending reminder emails. Following up on the follow-ups. Opening files to find last month's statement uploaded instead of this month's. Tracking everything in spreadsheets that fell apart by day five. Some were paying assistants specifically to send reminder emails a human doing nothing but asking people to send a PDF.
One thread that stuck with me was a bookkeeper describing a client she'd had for eighteen months lovely person, always paid on time who simply could not remember to send documents without three follow-ups. Every single month. She said she felt like a debt collector. Another post described someone who had tried three different portal tools, all of which required clients to create accounts on platforms they'd never heard of. Eight out of eleven clients called to ask if it was safe. She went back to email.
The pattern was clear: the tools that existed either required too much from clients, cost too much per client as practices grew, or were bolted onto accounting software that half the market didn't use. Nobody had built something that treated document collection as its own problem worth solving properly.
That's what I set out to fix. I applied my background in OCR, vision models, and large language models to build an automated pipeline that catches wrong documents before they reach the bookkeeper verifying document type and period at upload, not after. The rest of the product is built around the same principle: remove friction at every step, automate everything that can be automated, and make sure clients never have to create an account or learn a new tool.
Pockclient is the result. Built by an ML engineer who saw a problem that deserved a real technical solution and had the background to build it.