# AMPLY Discovery

**Canonical:** https://apis.io/providers/amply-discovery/  
**Website:** https://amplydiscovery.com/  
**APIs profiled:** 0

AMPLY Discovery is a UK (Belfast, Northern Ireland) biotechnology company turning the roughly 98% of the genome largely ignored by drug developers — the "dark genome" — into a pipeline of first-in-class therapeutics. The company pairs six AI/computational discovery engines with two wet labs in a closed loop between silicon and bench to find novel antimicrobial and therapeutic candidates targeting drug-resistant pathogens and complex diseases. AMPLY is a Techstars portfolio company and has been backed by Innovate UK, Invest NI, QUBIS and other UK/NI innovation programmes. It is tracked in the API Evangelist network as a company profile; AMPLY Discovery publishes no public developer API, documentation, SDKs, or machine-readable API surface at this time.

## Kin Score — 5.5 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 5.5).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Tags

Company, Biotechnology, Drug Discovery, Artificial Intelligence, Genomics, Pharmaceuticals, Therapeutics

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/amply-discovery/). Scores are computed from the provider's own public artifacts under a published rubric.