AI + R&D
R&D acceleration with human oversight
We support research teams with synthesis, patent landscaping, and rapid prototyping without compromising human judgment.
R&D workflows
From idea to prototype, faster
Our agents summarize research, surface patterns, and generate structured briefs for human review.
- Research synthesis and literature summaries.
- Patent landscape mapping and prior art review support.
- Prototype planning and documentation drafts.
- Human verification required for every decision point.
Automate the repetitive. Protect the human.
Where Ed plugs in
Sources, tools, and provenance the way research teams actually work
Ed reads the literature and lab data your team already relies on — and keeps an auditable trail from every claim back to its source, so a reviewer can trust the synthesis.
Literature synthesis with citations
Ed searches PubMed, arXiv, and patent corpora, clusters findings, and drafts a structured review where every assertion links back to the source document — no unsourced claims for a scientist to chase down.
Prior-art & freedom-to-operate support
Map the patent landscape around an invention, surface the closest prior art with claim-level context, and assemble a disclosure draft — with a patent attorney reviewing before anything is filed.
Experiment design & ELN integration
Draft protocols, propose DOE matrices, and write structured entries back to electronic lab notebooks like Benchling — so the experiment record is captured as the work happens, not reconstructed later.
Analysis & reproducible notebooks
Generate and run Python or R analyses on instrument and assay data, returning versioned notebooks and figures — the methodology is transparent and rerunnable, not a one-off result from a black box.
IP provenance & confidentiality
Proprietary data and unpublished results stay walled off from any training use, access is role-scoped, and Ed records the lineage of every generated artifact — protecting inventorship and trade secrets.
Memory across the program
Ed retains what was tried, what failed, and why — across months of a research program — so negative results inform the next experiment instead of being silently repeated by the next hire.
Why Ed — not just AI
Why R&D teams need Ed in the loop
Discovery is a long-horizon game of connecting scattered knowledge. Ed remembers every thread and synthesizes across all of it.
Nothing gets forgotten
Hypotheses, dead ends, and results accumulate in Ed's governed memory, so the team builds on prior work instead of relitigating it.
Synthesis at scale
Ed cross-references papers, patents, and internal data to surface connections that would take humans months to find.
Provenance you can defend
Every insight traces back to its source — essential for IP, peer review, and trust.
The difference: generic AI forgets between conversations and resets to zero. Ed runs on Memory Statue v2.6 — Prismatic Recall: persistent, governed, auditable memory and long-horizon operation, with a human in the loop where it matters.
Re-discovering what you already knew is the most expensive work in R&D.
Ready when you are
Support your innovation pipeline
We design AI copilots that respect IP, provenance, and human decision-making.