We make¹ scientists and deep tech startups AI-native².

Read the entire published body of a field overnight and return a structured map of what is known, what is contradictory, and what is missing, then generate testable hypotheses and surface analogies across disciplinary silos.

Thousands of papers read overnight and returned as a structured gap map. Systematic screening and extraction done with agents running in parallel. Every unresolved contradiction in a subfield enumerated on demand, with analogies drawn across every field at once.

Extract quantitative property data from a fragmented, multilingual literature and propose specific candidate compositions, molecules, or genes, including underexplored options found by analogy across material and biological classes.

Property data extracted from full texts and underexplored composition spaces flagged in days. All published SAR for a drug target synthesized and ADMET liabilities predicted in hours. Candidate sorbents, catalysts, electrolytes, and resistance genes proposed by analogy.

Read thousands of patents to map claim scope across whole portfolios, identify prior art and freedom-to-operate (FTO) gaps, and propose design-arounds for blocking patents.

Claim scope mapped across full portfolios in days, with design-arounds for blocking patents. Literature and patents mined together to map prior art, find FTO gaps, and propose novel candidates.

Design biological systems, including protein and enzyme variants, metabolic pathways, genome-scale models, gene edits, and crop crosses, by synthesizing structural, mutagenesis, homolog, and field-trial data before any wet-lab work begins.

Position-specific protein mutability returned in hours. Pathway designs and enzyme efficiencies synthesized to route around competing drains. CRISPR guide design, off-target prediction, and regulatory class combined in one pass.

Turn raw, high-volume measurement data (images, spectra, omics layers, sequences, and free-text records) into scientific conclusions, read against literature benchmarks.

Imaging scored at scale by vision models and read against literature benchmarks. Pathway enrichment and hypotheses generated automatically from multi-omic data.

Turn plain-language specifications into working domain-specific code (hardware description, verification testbenches, bioinformatics pipelines, and robot control programs) so that non-programmers can produce it.

Whole register-transfer-level (RTL) modules scaffolded from plain-language specs. Testbench skeletons, assertions, and coverage models generated from plain-language test plans. RNA-sequencing (RNA-seq) and single-cell pipelines generated, debugged, and documented.

Interpret simulation or experiment results, propose the next parameters to try, and search large design or route spaces in a closed loop, so optimization runs faster than humans can iterate, and select the best option scored against full criteria.

Electronic-design-automation (EDA) reports interpreted and next parameters proposed, collapsing weeks of iteration into days. Experiment results read and the next experiment proposed in a closed loop, 24/7. Trade studies, dispatch, and route selection grounded in full precedent.

Synthesize heterogeneous, multimodal operational data (sensor streams, logs, metrology, telemetry, maintenance history) against a knowledge base to rank root causes of failures and predict failures before they happen.

Statistical-process-control (SPC) data, tool logs, and maintenance history synthesized at once, with root causes in hours. Anomalies matched to fleet-wide failure signatures for remote diagnosis without a dispatch. Sensor health read against failure signatures to predict useful life and time maintenance exactly.

Before an expensive run or design is committed, enumerate the ways it can fail (failure modes, hazards, scale-up pitfalls) by synthesizing analogous prior cases, and propose mitigations up front.

Failure modes and mitigations for analogous reactions synthesized to quantify risk before the first large run. FMEA drafts built from failure histories in hours, surfacing modes that bias usually hides.

Make decades of fragmented, multilingual, classified, half-digitized, or about-to-retire engineering knowledge fully queryable, especially multi-decade materials-qualification archives, and identify the gaps systematically.

Multilingual, multi-decade data synthesized in full. Qualification gaps identified systematically. Make retiring expertise permanently queryable.

Continuously check artifacts and data streams against rulebooks, specifications, and acceptance criteria (design rules, requirements, certificates, safety signals), flagging only the exceptions and turning periodic manual review into a live process.

Design-rule queries answered instantly and violations caught at schematic entry rather than sign-off. Traceability matrices built and kept current from spec documents, with changes propagated downstream. Certificate values extracted and compared to limits, flagging only exceptions. Adverse-event patterns synthesized continuously, turning quarterly review into a live process.