Autonomous Research Engine
for Computational R&D Teams
From literature to executed experiments and novel findings in days, not years.
One system produced a full manuscript with zero human intervention in the loop
We pointed the engine at computational neuroscience with no prior expertise in the field. It autonomously scanned the literature, identified a gap, designed 900 experiments across 10 biological organisms, ran statistical analysis, and produced a complete manuscript with methods, results, and figures.
The paper was evaluated by an independent reviewer with NeurIPS experience who confirmed it meets standard publication benchmarks. Currently under review for PNAS.
Ingests literature corpus across 50+ scientific categories. Finds unaddressed questions and cross-domain gaps no single team would spot.
Produces testable hypotheses ranked by novelty and feasibility. Each validated through adversarial review before proceeding.
Writes code, runs computational models, and analyzes results on GPU infrastructure. Real experiments, not suggestions.
Internal adversarial review filters weak findings. Delivers comprehensive analysis with experiment protocols and manuscript output.
Research Discovery, Delivered
From literature to validated findings and experiment protocols in days, not months.
What you get
- Gap analysis across 50+ scientific categories
- 10+ ranked research hypotheses
- Cross-domain connections from adjacent fields
- Adversarial validation pipeline
- Designed experiment protocols with baselines
- Comprehensive PDF analysis report
Delivered in 3 business days. 10M+ papers analyzed at your request.
Try it now
Pre-Seed
We are raising a pre-seed round to scale compute infrastructure and close first paid pilots. If you are an investor, angel, or accelerator, we would love to connect.