Datacurve is a San Francisco-based AI infrastructure company that positions itself as "the data engine for frontier AI," building high-quality, expert-annotated datasets, reinforcement-learning environments, long-horizon agent tasks, benchmarks, and supervised fine-tuning demonstrations used to train and evaluate frontier AI models. Its offerings include off-the-shelf and custom datasets, agent-trajectory capture (tool calls, pivots, recovery attempts), and domain-sensitive evaluations across software engineering, data science, cybersecurity, machine learning, and research. Datacurve is backed by Homebrew and publishes research such as the DeepSWE long-horizon coding benchmark. The company sells through direct engagement (contact@datacurve.ai) and currently exposes no public API, developer portal, or SDKs.
Datacurve is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine Learning, Datasets, and Reinforcement Learning.
Regulatory Posture applies to this provider. Its tags matched the
Horizontal (data, software, accessibility, platform) regime, so
Regulatory Posture carries 15 points of the composite.
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Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero:
never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and
several others — scorable at all.
The six quality facets above are damped to 85 points between them,
because the conditional facet above carries the other
15. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 85% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
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aid: datacurve
deliveryModel:
model: unknown
open_source: false
commercial: false
callable_host: false
label: Delivery model not determined — needs a product licence on record
confidence: low
source:
- none
generated: '2026-08-28'
method: derived
accessModel:
pricing: unknown
onboarding: unknown
trial: false
try_now: false
public: false
label: Unknown
confidence: low
source: []
generated: '2026-07-22'
method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/datacurve.png
name: Datacurve
description: Datacurve is a San Francisco-based AI infrastructure company that positions itself as "the data engine for frontier
AI," building high-quality, expert-annotated datasets, reinforcement-learning environments, long-horizon agent tasks, benchmarks,
and supervised fine-tuning demonstrations used to train and evaluate frontier AI models. Its offerings include off-the-shelf
and custom datasets, agent-trajectory capture (tool calls, pivots, recovery attempts), and domain-sensitive evaluations
across software engineering, data science, cybersecurity, machine learning, and research. Datacurve is backed by Homebrew
and publishes research such as the DeepSWE long-horizon coding benchmark. The company sells through direct engagement (contact@datacurve.ai)
and currently exposes no public API, developer portal, or SDKs.
url: https://raw.githubusercontent.com/api-evangelist/datacurve/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- homebrew
x-tier: stub
x-tier-reason: portfolio-lead
x-enrichment:
last_run: '2026-07-18'
status: no-public-api-surface
notes: Enrichment probed the site plus the well-known and package-registry surface. Datacurve has no public API, developer
portal, docs, SDKs/packages, or event surface, so most artifact types are N/A (not penalized). Only the domain-security
probe and an identity/discoverability pass yielded real data.
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Artificial Intelligence
- Machine Learning
- Datasets
- Reinforcement Learning
- Benchmarks
- LLM Training
- AI Infrastructure
- Data Annotation
tags_raw:
- Company
- Ai
- Machine Learning
- Datasets
- Reinforcement Learning
- Benchmarks
- LLM Training
- AI Infrastructure
- Data Annotation
- Machine-Learning
apis: []
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
- FN: APIs.json
email: info@apis.io
common:
- type: Website
url: https://datacurve.ai
- type: Products
url: https://datacurve.ai/products
- type: Research
url: https://datacurve.ai/research
- type: Careers
url: https://datacurve.ai/careers
- type: DomainSecurity
url: security/datacurve-domain-security.yml
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