The human layer behind your models
Annotation, model evaluation and human-in-the-loop review, delivered by a trained team that scales with your pipeline.
Models need labelled data, ranked outputs and reviewed edge cases, continuously. That work is high volume, quality sensitive and impossible to hire for at speed.
Crowd platforms give you volume without consistency. An in-house team gives you consistency without volume. A dedicated trained team gives you both.
How we help AI & Data Operations teams
Two services, applied to the work that slows your team down.
Batch hiring against a project, so paying per campaign usually fits best.
Job adverts written and posted
Adverts written to your tone and posted across your chosen boards, refreshed and expired on schedule.
Application screening
Every application reviewed against your criteria and returned as a ranked shortlist with reasons. A specialist reviews every borderline case.
Candidate sourcing
Long lists built against your brief, with contact details verified before they reach you.
Interview coordination
Scheduling across time zones, confirmations, reminders and rescheduling handled end to end.
Reference and background checks
Requested, chased and logged, with every response filed against the candidate record.
Candidate compliance
Work authorisation and document verification under your local rules, with a complete audit trail.
Offer and onboarding paperwork
Offer documents prepared, signatures chased and onboarding packs completed before day one.
Applicant tracking upkeep
Your hiring system kept clean: records updated, duplicates merged, pipelines accurate.
Data labelling and annotation
Text, image, video and audio labelled to your guidelines, with inter-annotator agreement tracked.
Model output evaluation
Responses rated and ranked against your rubric, with reviewer notes on every disagreement.
Human-in-the-loop review
Live review queues for flagged outputs, cleared within your service window.
Content moderation
Policy review at volume, with escalation paths for ambiguous cases.
Training data QA
Sampling, audit and correction passes across labelled datasets before they reach training.
Transcription and classification
Audio transcribed and text classified to your taxonomy, at consistent quality.
We work in the tools you already use.
No migration, no new platform, no retraining. We work inside your existing systems under your own access controls.
What this looks like in practice
Illustrative exampleA 12-person annotation team
The challenge
An AI company whose labelling backlog sets the pace of model releases, with quality varying between crowd vendors.
What we do
- A trained annotation team working to one guideline set
- A QA layer sampling output before delivery
- Capacity increased in blocks as the pipeline grows
What this work is costing you
Adjust the numbers to match your operation.
An estimate. Change it to match your process.
Which service fits your team?
Choose the model that matches how your operation runs.
Recruitment Back Office
Screening, compliance, onboarding and placement admin, delivered inside your own ATS.
Offshore Team Solutions
Your own dedicated team, live in 7 days. Open 24/7 for any time zone.
Take the admin off your team
Tell us what's slowing your team down and we'll show you how we'd take it on.