Sypro Tech builds AI products for specific industries. Each system takes on the most congested stretch of its own workflow — and industry after industry, the congestion comes down to the same three things.
Quant TradingInvestment ResearchContent GrowthSite SelectionPublic ProcurementFootwear ProductionLearningAutonomous Dev
Give it a question and it decides what to look up and when the evidence is enough. Every gap it fills during multi-hop reasoning leaves a trace, so a conclusion comes back with a confidence score and with the passage that supports it.
State the requirement in conversation; the system breaks it down, writes the code, runs the tests and produces the docs. Once you approve the merge it deploys to a live URL — what you get is a running product, not a pile of code.
Upload a document and get interactive material in 30 seconds: questions across Bloom’s six levels, review scheduled by FSRS, concepts wired into a knowledge graph. The public library already holds more than 4,000 question sets and documents — open and read, no login.
Two signal tracks — one follows momentum, one digs for pain points — and a topic is only chosen after they cross-check. Drafts go through four distillation rounds and de-AI detection, then dual human review before anything ships.
Each one targets the core decision problem of an industry, from data collection all the way through to execution.
This company is its own first user. Thesora does the research, Yanshi does the delivery, InsightForge does the operating — research feeds requirements, requirements feed delivery, and what the market says feeds the next version.
What to build gets researched first, by Thesora: the industry, the competitors, the policy landscape, the literature. Conclusions come back with evidence, sources and a confidence score — so requirements rest on checkable facts, not on impressions from a meeting room.
Requirements go into Yanshi, which breaks them into tasks, writes the code, runs the tests and produces the docs. People check two things at the gates: is the direction right, and is the result shippable. Nobody watches line by line.
Once a product ships, InsightForge takes over: dual-track signals pick the topic, four distillation rounds write it, two rounds of human review clear it, then it gets rewritten to each channel’s voice. Search visibility, competitor moves, lead attribution and customer complaints all come back the same way.
Rejected approvals, production incidents, user corrections and market response are traced together into recurring patterns, then — once approved — become rules the next round has to follow. All four stages share one task record, so nothing is lost in the handoff.
The changelog updates monthly. Three from this month:
New academic report type wired to Crossref, OpenAlex, arXiv and Semantic Scholar; competitive research shipped alongside it.
Traces recurring failure patterns from rejected approvals, task errors, incidents and user corrections into rule proposals that take effect after human approval.
Generates slides, documents, deep reports and charts from local material and research results, anchored to multiple sources across iterations.
Tell us about the decision problem in your industry that keeps recurring and has never been solved properly. Let’s see whether it can become a system.