Reproducible by Design
Every run captures its inputs, tools, and decisions in a tamper-evident trail — so any finding can be replayed and defended, exactly.
SigmatoeOS · v0.1
The agentic operating system for life sciences R&D
Sigmatoe turns AI from a copilot into an autopilot. A Scout Mesh of autonomous agents orchestrates dry lab computation and wet lab automation — moving from hypothesis to discovery in hours, with every action deterministic, traceable, and compliant.
- Hypothesis to finding, not weeks
- HoursHypothesis to finding, not weeks
- Specialized scout agents, running in parallel
- 4Specialized scout agents, running in parallel
- Architecture layers, fully auditable
- 5Architecture layers, fully auditable
Scout Mesh
Integrates with the tools scientists already use
RDKitAlphaFold 3BenchlingJupyterSchrödinger SuiteBLAST+Hamilton STARTecan FluentOpentronsCellarioRDKitAlphaFold 3BenchlingJupyterSchrödinger SuiteBLAST+Hamilton STARTecan FluentOpentronsCellario
The pipeline, live
One continuous flow, from question to defensible answer
Sigmatoe orchestrates the entire research loop as a single, observable pipeline. Watch a hypothesis flow through the Scout Mesh into dry and wet lab execution and emerge as a fully traceable finding.
ΣSigmatoeOS
01
Hypothesis
A research question enters the system
02
Scout Mesh
Agents plan and reason in parallel
03
Dry Lab
Docking, ADMET, and simulation
04
Wet Lab
Protocols run on lab robotics
05
Auditable Finding
Evidence traced to its source
From copilot to autopilot
Legacy systems take weeks. SigmatoeOS takes hours.
Most AI tools stop at suggestions, leaving scientists to stitch together pipelines by hand. SigmatoeOS is an agentic operating system that dynamically constructs and runs entire R&D pipelines, separating reasoning from execution so results are reproducible and defensible.
- Decomposes research questions into parallel, specialized work
- Converges on a single auditable finding with traced evidence
- Bridges dry lab computation and wet lab execution end to end
Why teams choose Sigmatoe
Serious science deserves a serious operating system
Four principles guide everything the Scout Mesh does — so your lab moves faster without ever trading away rigor.
Ask in Plain Language
Pose a hypothesis in a sentence. Sigmatoe parses intent, constraints, and success criteria — no scripting or pipeline wiring required.
Agents That Collaborate
Specialized agents for docking, ADMET, literature, and assay design work in parallel, then converge on a single, coherent answer.
Transparent Orchestration
Watch reasoning and execution stay cleanly separated, with deterministic tool calls you can inspect at every layer of the mesh.
How it works
From a sentence to a defensible discovery
A single agentic loop replaces the brittle chain of scripts, handoffs, and spreadsheets that slows modern research to a crawl.
- Step 01
Ask a research question
Pose a hypothesis in plain language — "find selective inhibitors for target X with favorable ADMET." Sigmatoe parses intent, constraints, and success criteria.
- Step 02
The Scout Mesh plans
The orchestrator decomposes the question into parallel tasks and dispatches specialized agents — docking, ADMET, literature, and assay design — each with the right tools.
- Step 03
Dry and wet lab execute
Deterministic tool calls run computational pipelines, then translate winning designs into executable protocols for Hamilton, Tecan, and Opentrons instruments.
- Step 04
Receive an auditable finding
Results converge into a single answer with every decision, dataset, and citation captured in a tamper-evident, 21 CFR Part 11-ready audit trail.
See it in action
Drop it in, watch it run, act on the result
From a single API call to a fully audited finding — Sigmatoe keeps a human in the loop at every step.
Integrate in minutes
Drop our SDK into your stack with a few lines of code.
await sigmatoe.run({
question: "Find selective
inhibitors for TARGET_X",
tools: ["docking", "admet"],
}); 10 min setupREST API
Agent Run
Live14:32:15 · docking
Ranked 1,204 poses; 18 candidates cleared ADMET filters…
14:32:18 · admet
14:32:25 · literature
Quality
Reproducibility9.2
Coverage8.7
Confidence9.0
Flags
Hallucination Clear
Data leak Clear
Bias Clear
Act with confidence
A single, traceable result — delivered with full context.
Finding ConvergedHigh Confidence
18 candidate inhibitors ranked and validated. Every step is recorded and ready for review.
- Run ID:
- run_8f2a
- Confidence:
- 9.2
- 21 CFR Part 11 audit trail
- You review, approve, export
Explore the full platform
Scout Mesh
A mesh of specialized agents, working in parallel
The Scout Mesh decomposes a research question into specialized sub-agents that run analyses simultaneously, then converge on a single, auditable finding.
Σ
Docking Scout
Runs structure-based docking across ligand libraries and ranks binding poses.
Σ
ADMET Scout
Predicts absorption, distribution, metabolism, excretion, and toxicity profiles.
Σ
Literature Scout
Synthesizes prior art and evidence with citations traced to source.
Σ
Assay Design Scout
Proposes and validates assay parameters ready for wet lab execution.
Architecture
Five layers that separate reasoning from execution
Every action is deterministic and verifiable — by design, not by convention.
01
Audit & Compliance
A cryptographically secure audit trail records every decision and action for regulatory review.
02
Orchestration
Dynamically constructs and runs R&D pipelines, decomposing questions into parallel work.
03
Agent Fabric
The Scout Mesh of specialized autonomous agents that reason, plan, and converge on findings.
04
Tool & Data Integration
Connects to cheminformatics, dry lab pipelines, and your existing scientific data sources.
05
Wet Lab Interface
Translates experimental designs into executable protocols for automation instruments.
Use cases
Built for the hardest problems in R&D
Wherever computation meets the bench, Sigmatoe closes the loop — turning weeks of coordination into an autonomous, auditable workflow.
Small-molecule discovery
Screen vast ligand libraries, rank binding poses, and filter for drug-likeness before a single reaction is run.
Target identification
Synthesize genomic and proteomic evidence with cited literature to prioritize the most promising therapeutic targets.
Assay development
Design, simulate, and validate assay parameters, then push executable protocols straight to lab automation.
Green & synthetic biology
Optimize enzyme and strain candidates across dry-lab prediction and wet-lab confirmation in one continuous loop.
How it's built
Autonomy that compounds across the lab
- From a research question to an auditable finding
- HoursFrom a research question to an auditable finding
- Specialized scouts run their analyses at once
- In parallelSpecialized scouts run their analyses at once
- Of decisions and actions captured in the audit trail
- 100%Of decisions and actions captured in the audit trail
- Deterministic architecture layers, end to end
- 5Deterministic architecture layers, end to end
Integrations
Plugs into your existing scientific stack
An Embed SDK connects Sigmatoe directly into the tools your team already lives in — like Benchling and Jupyter — so scouts can pull data and hand back results without any manual glue code.
Cheminformatics
- RDKit
- AlphaFold 3
- OpenBabel
- DataWarrior
Dry Lab Pipelines
- BLAST+
- Schrödinger Suite
- Jupyter
- Nextflow
Wet Lab Automation
- Hamilton STAR
- Tecan Fluent
- Opentrons
- Cellario
Data & Notebooks
- Benchling
- Hamilton Venus
- LabArchives
- Private Cloud
Security & compliance
Built for regulated industries
Enterprise-grade controls so you can adopt autonomous R&D with confidence.
21 CFR Part 11 Ready
Cryptographically secure, tamper-evident audit trail for every action.
SOC 2 In Progress
Controls and monitoring aligned to SOC 2 Type II standards.
HIPAA Aligned
Safeguards for handling protected and sensitive research data.
On-Premise Deployment
Deploy fully within your own private cloud or on-premise environment — your data never leaves your control.
“We started Sigmatoe because researchers were spending more time wiring pipelines together than actually doing science. The goal is simple: ask a question in plain language, and get back a finding you can defend.”
Principles
The commitments behind the platform
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.
FAQ
Questions, answered
Is my research data ever used to train shared models?
No. Customer data is fully isolated and is never used to train shared or foundation models. Your data stays yours — full stop.
Can Sigmatoe be deployed on-premise?
Yes. SigmatoeOS can deploy entirely within your own private cloud or on-premise environment, so sensitive research data never leaves your control — with the same agentic capabilities available in our managed cloud.
How do you ensure results are reproducible?
We separate reasoning from execution and prefer deterministic tool calls over generative answers. Every action, dataset, and decision is recorded in a tamper-evident audit trail for full reproducibility.
Which lab instruments and tools does it integrate with?
Sigmatoe connects to cheminformatics tools like RDKit and AlphaFold 3, dry-lab pipelines such as Nextflow and the Schrödinger Suite, and wet-lab automation from Hamilton, Tecan, and Opentrons — plus notebooks like Benchling and Jupyter.
What compliance standards do you support?
Sigmatoe is built for regulated industries with a 21 CFR Part 11-ready audit trail, SOC 2 Type II controls in progress, and HIPAA-aligned safeguards for sensitive data.
Bring autonomy to your R&D pipeline
Join the teams moving from hypothesis to discovery in hours. Request access and we'll build a deployment plan for your lab.