Mission Brief
Today, most AI initiatives never make it into production—especially in techbio, biotech, physical AI, and AI4Science/AI4Engineering domains like longevity, virtual cells, clinical analytics, and biomanufacturing.
ArcellAI is the agentic data and context layer for AI-native R&D across techbio, biotech, physical AI, and scientific and engineering domains. Our agents ingest, structure, and operate on multimodal lab, clinical, operational, and IP data—unifying ingestion, provenance, and orchestration so models, scientific software, and real-world systems actually deploy, interoperate, and improve over time.
Our mission is to accelerate scientific progress to the speed of software and enable accessible, affordable longevity for everyone.
In techbio, biotech, physical AI, and AI4Science/AI4Engineering—from longevity and virtual cells to clinical analytics, bioengineering, and biomanufacturing—most AI never leaves the lab. Models look strong in notebooks and slide decks, but break against messy, multimodal, regulated reality.
The failure modes rhyme everywhere: fragmented data silos, brittle one-off pipelines, no trustworthy provenance, and no orchestration layer that makes AI agents safe enough to operate on real R&D and engineering systems.
ArcellAI is built to close this gap: an agentic data layer that sits across lab, software, and model infrastructure, so scientific and engineering AI is deployable, auditable, and continuously improving.
Field Report
Observed failure patterns
ArcellAI response
See how ArcellAI transforms data workflows for R&D teams
End-to-end automation across ingestion → transformation → lineage → orchestration → model invocation. Standardized tool APIs and deep integrations turn your data infrastructure into autonomous scientific and engineering workflows. A self-driving semantic layer ensures metrics and calculations remain consistent across teams. Every run versions data, captures lineage, and strengthens your provenance graph.
Automates ingestion → cleaning/transformation → lineage → orchestration across your R&D stack.
Purpose-built agents with domain-specific intelligence via context engineering and tool use.
Versioned datasets, transformation lineage, and auditable workflows captured in a provenance graph lightly anchored on distributed ledger rails for tamper-evident, long-range agent memory.
Autonomously defines and centralizes research metrics, experimental KPIs, and statistical calculations—ensuring consistency and governance across all R&D analytics.
ReAct-style planning with coding and tooling agents orchestrated over foundation models and retrieval—decomposing goals into safe, multi-step pipelines backed by RAG, provenance-aware anchoring, and a governed universal latent space.
API-first, MCP-aligned tool layer across databases, notebooks, LIMS/ELN, lab robotics, and enterprise systems—all exposed as standardized agent tools.
Versioned datasets and transformation lineage anchored on distributed ledgers for tamper-evident lineage, smart-contract-powered reproducibility, decentralized knowledge graphs, and immutable records that strengthen ArcellAI's data flywheel and long-range agent memory.
A visual data science and AI canvas for building and exploring complex workflows: natural-language-to-visual insights, cognitive cartography for mapping data landscapes, spatial and network intelligence for relationship graphs, and interactive, node-based analysis.
ArcellAI turns fragmented data work into autonomous, reproducible workflows—so your team can focus on discovery. Go from raw data to decisions in hours, not months.
The brilliant minds behind ArcellAI's revolutionary agentic data science platform.
Our team information will be revealed soon. Stay tuned for updates on the exceptional researchers and engineers building the future of autonomous data science.
The ArcellAI platform is built on the data view design and API-first paradigm introduced in the PyTDC publication at ICML 2025. PyTDC is a multimodal machine learning platform for biomedical foundation models that unifies distributed data sources and standardizes AI inferencing and benchmarking endpoints.
Ready to revolutionize your data science workflows? Let's discuss how ArcellAI can accelerate your research.