AI for R&D teams
who need to be right.

IGOR^AI searches by function, not by name. A packaging team working on thermal challenges for a 3 nm node, trying to dissipate heat at the die surface, ends up reading aerospace jet‑impingement cooling and HPC immersion‑cooling research alongside the microchannel literature they already know. The technology that solves your challenge is usually invented somewhere else first.
Findest finds it.

The Universe's browser extension captures findings from literature, supplier sites, and technical documentation as your team works. When a colleague is about to research a topic your team already investigated, the extension flags it. No more duplicate work across projects, sites, and locations.

IGOR^AI reads through your team's collected sources and returns synthesised answers, comparison tables, and structured technology descriptions. Every claim links back to the original paper or patent. A wafer-bonding question that used to take a senior engineer three weeks of structured reading is answered in an afternoon, with the sources cited inline.

Every question, answer, and source captured in the Universe stays available to the next person who picks up the project. When an engineer joins a team six months in, the reasoning is already in front of them. Decisions get made faster because nobody is reconstructing what their colleague already figured out.

A Findest sprint is where new teams are guided onto the Universe properly. Six weeks, real R&D challenges, and a Findest expert guiding your team through the platform end-to-end. By week six your team have built three deliverables themselves: a technology landscape, deep dives on the approaches that matter, and a requirements table that compares them against your KPIs. Your team learns the methodology by using it on work that counts.