Diraflow
Diraflow
From agentic task environments to safety red-teaming — we build premium data solutions that integrate deep human expertise with scalable technology to accelerate frontier AI development.
From LiDAR perception pipelines to agentic training environments — we collect, curate, and annotate the world's most complex AI training data.
Diraflow delivered STEM annotation quality we couldn't find anywhere else. Their mathematics contributors caught subtle errors that would have degraded our reward model significantly.
The agentic environment datasets they built were genuinely novel — not recycled from public sources. The quality bar is exceptionally high and turnaround was faster than promised.
Red-teaming at scale without compromising on adversarial creativity is incredibly hard. Diraflow solved it. They're our go-to safety data partner without question.
We designed 12,000 realistic software engineering tasks across Python, TypeScript, and Go — each with ground-truth solutions verified by senior engineers.
500 clinicians across three specialties ranked AI-generated medical responses — producing a high-signal RLHF dataset that improved clinical accuracy by 18%.
A deep-dive call to understand your model, use case, quality bar, and timeline. We design the taxonomy and task spec together — collaboratively.
We hand-pick contributors from our vetted network based on domain expertise, annotation style, and calibration performance on your task type.
A small pilot batch is reviewed together. We iterate on guidelines and calibrate contributors before committing to full production.
Full-scale production with multi-layer review, IAA monitoring, and weekly progress reports delivered directly to your team.
Versioned, documented datasets delivered in your preferred format. We remain available for follow-up batches and expansions.
Synthetic data has its place — but the frontier of AI capability is still defined by the quality of human-generated signal. We exist to make that signal accessible, at scale, without sacrificing the nuance that makes it valuable.
Every contributor goes through structured onboarding: credential review, domain knowledge test, and calibration tasks scored against gold-standard examples. During production, we monitor inter-annotator agreement continuously and remove contributors whose scores fall below threshold. Project leads conduct spot checks at regular intervals.
We typically work best on projects of 1,000 tasks or more. For smaller exploratory pilots, we offer a structured 200-task pilot package to test fit before scaling. Get in touch and we'll find an approach that works for your situation and budget.
Yes. All contributors sign NDAs before accessing any project materials. We can work within your preferred data handling environment — including air-gapped annotation setups, your own VPC, or Diraflow's SOC 2-aligned infrastructure. Data security is standard, not an add-on.
For well-defined tasks with clear guidelines, we can typically begin a pilot within 5–7 business days of scope sign-off. More complex projects requiring custom tooling or specialised contributor recruitment may take 2–3 weeks to spin up. We'll give you an honest timeline during scoping.
Absolutely. We work with research labs, universities, and non-profit AI organisations. We offer flexible engagement structures for academic budgets — reach out and let's talk about what's possible.
We deliver in whatever format your training pipeline expects — JSON, JSONL, CSV, Parquet, HuggingFace datasets, and more. Full schema documentation, versioning, and incremental or batch delivery depending on your workflow.
Yes. This is a foundational commitment at Diraflow — all work is produced by verified human contributors. Our QA pipeline includes AI-content detection checks, and any flagged output is reviewed and rejected before delivery. We can provide signed attestations on request.
Pricing depends on task complexity, required expertise, review depth, and volume. After scoping we provide a fixed per-task rate along with a total project estimate. We never upcharge mid-project — if scope changes, we re-quote transparently.
Yes. We produce original human content in 30+ languages with native-speaker contributors. For low-resource languages, we work with in-region partners and linguists to maintain cultural fidelity and correct dialect handling.
You do. All deliverables transfer to the client on payment, with full IP assignment. We retain no rights to re-use, re-sell, or reference your data in other engagements.
Yes. Many engagements pair training data with custom evaluation suites — including held-out benchmarks, scoring rubrics, and automated grading pipelines — so you can measure lift from the data you commission.
Absolutely. For partners with recurring needs we set up a dedicated pod — a stable group of contributors, a lead reviewer, and a project manager — so institutional knowledge compounds across projects.
Tell us about your project and we'll respond within one business day with initial thoughts and next steps.
We work with clients across North America, Europe, Africa, and Asia. No timezone is too cumbersome — we'll make it work.
We respond to all project enquiries within one business day. For urgent timelines, mention it and we'll prioritise.
Include your use case, approximate task volume, and desired timeline and we'll come back with a tailored proposal.
A world where artificial intelligence empowers everyone equally, operating transparently, ethically, and free from harm, making AI a trusted ally for all humanity.
To train and certify AI systems and their developers in safety-first practices, embedding fairness, accountability, and robustness at every stage of the AI lifecycle.
