We're rewriting how science gets done
Sigmatk builds the agentic operating system for life sciences R&D — turning autonomous agents into a trustworthy, auditable engine for discovery.
Our mission
Legacy R&D systems force scientists to spend weeks manually assembling pipelines, triaging results, and reconciling dry lab computation with wet lab execution. We believe that work should take hours — and that autonomy should never come at the cost of rigor.
SigmatkOS orchestrates a Scout Mesh of specialized autonomous agents that dynamically construct and run entire pipelines, from docking and ADMET prediction to assay design and instrument execution. Every action is deterministic, traceable, and built to meet the standards of regulated industries.
We're a company founded by scientists and engineers who were tired of watching great research stall on tooling. Our roadmap is co-developed directly with the researchers who use the platform every day.
Leadership
The people building Sigmatk span computational biology, distributed systems, lab automation, and compliance.
Stephanie Garcia
Founder & Chief Executive Officer
Stephanie founded Sigmatk in 2025 after a decade building computational drug discovery platforms. She leads the vision of moving AI from copilot to autopilot in regulated R&D.
Amara Okonkwo
Chief Technology Officer
Amara architects the Scout Mesh agent fabric and orchestration layer, with a background in distributed systems and reproducible scientific computing.
Daniel Reyes
Head of Wet Lab Automation
Daniel bridges dry and wet lab workflows, translating computational designs into executable protocols across Hamilton, Tecan, and Opentrons instruments.
Priya Nair
VP of Compliance & Security
Priya leads audit, compliance, and on-premise deployment, ensuring every action meets 21 CFR Part 11 and enterprise security expectations.
Milestones
- 2025Sigmatk Ltd is founded by Stephanie Garcia.
- 2025The first Scout Mesh prototype orchestrates a dry lab pipeline end to end.
- 2025Early access opens for design partners, with the Embed SDK in private preview.
- 2025Private-cloud and on-premise deployment arrive alongside a 21 CFR Part 11-ready audit trail.
What we stand for
Provenance over plausibility
Every finding is traceable to its source. We surface evidence, not guesses.
Your data is never trained on
Customer data is isolated and never used to train shared models. Full stop.
Deterministic tool calls
We prefer verifiable, deterministic execution over LLM-generated answers.
Built with scientists
Our roadmap is co-developed directly with the researchers who use it.