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Lila Sciences website screenshot

Lila Sciences

Lila Sciences is an AI company founded in 2023 that is building what it calls Scientific Superintelligence: an autonomous system that runs the scientific method end to end by generating hypotheses, designing experiments, executing them in physical AI Science Factories (autonomous robotic laboratory networks), and learning from the resulting experimental data. Rather than training on internet text, Lila trains a scientific reasoning model on experimental data, coupling it to scalable verifiers and instruments such as molecular dynamics simulators, protein structure predictors, quantum chemistry solvers, and gene editors, then optimizing the policy with reinforcement learning. The company packages this as two commercial offerings: Catalyst, positioned as an operating system for science that accelerates an organization's existing research, and Creation, a partnership model for generating new discoveries, launching products, and founding new companies. Lila works across therapeutics (mRNA, proteins, antibodies, cell therapies, small molecules), advanced materials, chemicals, energy and environment, oil and gas, aerospace and defense, and biotech. It has raised roughly $550M ($200M seed announced March 2025 and a $350M Series A closed in October 2025) from investors including General Catalyst and NVIDIA, at a reported valuation above $1.3B, and collaborates with NVIDIA on the BioNeMo Agent Toolkit. Lila operates from Cambridge MA, San Francisco CA, and London UK. As of this profile Lila publishes no public developer API, developer portal, SDKs, or machine-readable API artifacts; this entry is a company identity record in the API Evangelist network.

human only

Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.

Kin Score

API Evangelist profiles Lila Sciences the way a machine reads it — 1 machine-readable artifact, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Lila Sciences scores 14.3/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 14.3/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.4 / 20
Commercial Clarity 4.2 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Regulatory · Health 4.6 / 15
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Lila Sciences

Each block below is one kind of artifact we hold for Lila Sciences. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Lila Sciences Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Every other property we hold for Lila Sciences — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Access & Security 1

Authentication, authorization, and security posture

Operate 1

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Other 1

Properties that don't map to a standard resource type

← All providers · Data indexed from github.com/api-evangelist/lila-sciences · machine-readable index on apis.io