Managed AI trainers, LLM evaluators and benchmark authors for AI labs and data partners. We vet, review and pay every expert. You get one point of contact. 2,500+ evaluation tasks authored, 90% task acceptance rate, 4.89/5 average quality rating, 9+ benchmarking programmes delivered.
The problem
Experts churn mid-batch. Strong contributors get banned, ghosted or pulled to the next queue, and throughput drops the week you need it most.
Grading drifts. Crowd-scale review hides inconsistent scoring, so your team ends up re-checking work it already paid for.
Nobody owns the outcome. Marketplaces send profiles, not results. When quality slips, the problem lands back on your desk.
FynoLabs owns the people layer: sourcing, vetting, review and payment. Managed, not brokered.
Who we work with
For AI labs: Benchmark-grade tasks and evaluations. Coding-agent tasks, research reproduction and rubric-based evaluation, written and reviewed by people who have shipped them before.
For AI data partners: Vetted capacity, on demand. A managed pod that plugs into your queues when a programme outgrows your bench. We vet, review and pay. You get one invoice.
For enterprise AI teams: Expert evaluation before launch. Domain experts test your model or agent against your own rubric, so failures surface before your users find them.
What we deliver
Coding-agent benchmarks: Terminal-Bench and SWE-bench-style tasks: a real repo or shell, a reference solution and tests that prove it.
Research reproduction: PaperBench-style tasks that check whether an agent can rebuild a published result from the paper alone.
Model evaluation & RLHF: Preference ranking and rubric-based grading of model outputs across code, reasoning and tool use.
Long-horizon agent tasks: Multi-step work that needs planning, tool use and recovery from mistakes, with clear pass criteria.
STEM & expert reasoning: PhD-level questions in life sciences and STEM, with worked answers a specialist has checked.
Quality: four checks on every task
Trial task: Every expert passes a scored trial against your rubric before touching live work.
Peer review: A second specialist reviews every item. Not a sample, every item.
Calibration: A senior reviewer samples each batch and resets the bar when grading drifts.
Sign-off: Nothing ships without a final human call. Work below the bar goes back to its author.
How it works
Scope (first call): We agree the rubric, domains and acceptance target with you.
Pilot (weeks 1–2): 5–10 experts on one queue, paid, measured against that target.
Scale (weeks 3–4): Add vetted experts in steps once the pilot hits target.
Run (ongoing): We onboard, review and pay. You get a weekly report and one invoice.
Why FynoLabs
Who you work with: One programme lead, one channel (open marketplaces: hundreds of individual profiles).
Vetting: A scored trial on your rubric (open marketplaces: cv and quiz screens).
Review: A second review on every item, plus senior calibration (open marketplaces: spot checks, if any).
Rejected work: Returned to its author before delivery (open marketplaces: your team finds and re-checks it).
Payments: One invoice, and we pay every contributor (open marketplaces: many contractors to pay).
Proof: Published quality numbers (open marketplaces: headcount claims).
Frequently asked questions
What does FynoLabs do for AI labs and AI data partners?
We supply and manage specialist contributors for AI training data and model evaluation: AI trainers, LLM evaluators, benchmark and task authors, and research reviewers. We vet, onboard, review and pay them. You get one point of contact.
What kind of AI training work do you cover?
RLHF and preference ranking, rubric-based evaluation of model outputs, coding-agent tasks in the style of SWE-bench and Terminal-Bench, research reproduction in the style of PaperBench, long-horizon agent tasks, STEM reasoning questions and expert review of design outputs.
How fast can you staff a project?
A pilot team of 5 to 10 experts usually starts within days. We then add vetted experts in steps across coding, data science, life sciences and STEM, and product design.
How do you keep quality high?
Everyone passes a scored trial task against your rubric before joining. A second specialist reviews every item, a senior reviewer samples each batch, and nothing ships without final sign-off. Our track record: 2,500+ evaluation tasks authored, a 90% acceptance rate and a 4.89/5 average quality rating.
Where is your team based?
FynoLabs is based in Robertsganj, Uttar Pradesh, India, and works remotely with clients worldwide. Our hours overlap European working days and US mornings.
Do you name your clients?
No. We work NDA-first and never name clients or programmes in public.
How do we start?
With a two-week paid pilot on one queue and an acceptance target we agree up front. Book a partner call at cal.com/fynolabs/partner-intro or email hello@fynolabs.si.
I am a domain expert. Can I join FynoLabs?
Yes. Engineers, data scientists, researchers, PhD scholars and designers can apply through our talent call at fynolabs.si/talent-call.