Remote / Global · AI Training & Quality Review
Stop managing annotators. Start shipping models.
Expert-reviewed AI training data delivered in 48–72 hours, with a direct line to your annotation team and a QA report that catches what Scale AI lets through.
Book your intake callSee how it works
Serving Remote / Global
- Founder-reviewed first batch on every project
- 48–72hr pilot turnaround
- Vetted annotator bench
- quality scores on file
- Direct Slack access to your team
- No platform contract
- start with 500 samples
Your annotation pipeline is eating your sprint capacity
Most ML teams at Series A–B companies are running the same improvised stack: three Upwork pools, a Google Sheet, a Slack channel no one checks, and a Scale AI account that charges enterprise rates to put your tickets in a queue. You spend 30–40% of every sprint chasing inconsistent output, manually spot-checking batches that should have been QA'd before delivery, and debugging label errors that are already in your training set. The problem is not that annotation is hard. It is that every large platform optimises for volume throughput, not annotator accountability. What corrupts your data is not complexity, it is the absence of a named person whose job is to care about your quality baseline.
How a TrainWise project actually runs
- 30-minute intake call You walk us through your task: what you are labelling, your label schema, edge cases, and quality bar. We produce a written task spec document the same day so nothing lives in someone's head.
- Annotator briefing and pilot batch The founder assembles a team of 3–8 reviewers from the TrainWise vetted bench, briefs them against your spec, then personally runs the first 500-sample pilot batch to set a documented quality baseline before a single task goes to the full team.
- Client sign-off before full delivery You receive the pilot batch alongside a QA diff report showing where errors were caught and corrected. You approve the baseline, or request a revision round, which is included. No surprises in the full batch.
- Ongoing delivery with daily async updates Full batch delivery runs through a shared Airtable and Notion workspace with daily async updates from the team. You have direct Slack access, no ticket queue, no account manager reading from a script.
Why TrainWise
QA baked in, not bolted on
Every batch is reviewed against your task rubric before it leaves our end. You receive a QA diff report with each delivery, showing what was caught and corrected. You are not the last line of defence.
A named team, not a platform queue
Your project is staffed by 3 to 8 pre-vetted annotators assembled specifically for your task type. You know who is doing the work. You can ask questions. That feedback loop is how quality stays consistent across months, not just the first batch.
Scoped and running in 48 hours
A 30-minute intake call is enough to produce a task spec, brief the team, and start the pilot batch. There is no procurement process, no platform onboarding, and no minimum commitment that makes starting feel like a risk.
Services
- Monthly Retainer — Standard $1,800 Up to 5,000 tasks per month across annotation, output quality review, or RLHF preference ranking. Weekly delivery batches, Slack access to the team, monthly QA summary report.
- Monthly Retainer — Scale $4,500 10,000–25,000 tasks per month, dedicated annotator pod, priority turnaround (24hr), custom rubric development, and monthly strategy call with founder.
TrainWise versus the alternatives
| TrainWise | The usual way | |
|---|---|---|
| Direct contact with annotators | Yes, Slack access to your named team | No, tickets go into a platform queue |
| Founder reviews first batch personally | Yes, every new project | No, assigned to an anonymous pool |
| QA report included with every delivery | Yes, errors caught before delivery | Inconsistent, errors often pass through |
| Pilot before committing to volume | Yes, start from a single batch | Often requires platform onboarding or minimum spend |
| Custom rubric built for your task | Yes, scoped on intake call | Generic guidelines applied at scale |
| Turnaround on first batch | 48 to 72 hours | Days to weeks depending on queue |
| Annotator vetting transparency | Documented quality scores on file | Platform-managed, not shared with you |
Who this is built for
TrainWise works best when there is a real annotation or QA problem to solve and someone on your side who can make a quick decision about scope. If you are managing data ops alongside model development and the two are constantly in conflict, this is the right conversation to have.
- ML leads at Series A to B startups with 5 to 30 engineers
- AI founders managing data ops without a dedicated team
- Independent researchers running fine-tuning or RLHF projects
- Enterprises piloting AI features who need an external QA layer first
- Teams who have already tried Upwork or Scale AI and hit a wall
One 30-minute call scopes your project. Your first batch ships within 48 hours.
No retainer required to start. Pilot Sprint available from £400.
Frequently asked questions
What types of annotation and QA tasks do you handle?
Text annotation, RLHF preference ranking, instruction-following evaluation, output quality review, classification and labelling, hallucination detection, summarisation QA, and multi-turn conversation review. If your task involves a human judgement call on model inputs or outputs, it is within scope. Bring the spec to the intake call and we will tell you within the hour whether it fits.
How does the founder QA process actually work?
On every new project, the founder personally reviews the first batch against the agreed rubric before it is delivered to you. This sets the quality baseline and catches any systematic errors in annotator interpretation early, before they propagate through the full dataset. Subsequent batches are reviewed by the founder on a spot-check basis with a QA summary included at delivery.
Can we start with a small pilot before committing to a retainer?
Yes, and that is the recommended path. A paid pilot batch lets you see the QA process in action, review the output against your existing baseline, and decide whether the quality justifies moving to monthly volume. It de-risks the decision on both sides. Ask about current pilot availability when you book the intake call.
What tools and formats do you deliver in?
Deliverables come in CSV, JSON, or JSONL depending on what your pipeline expects. The working process runs on Airtable, Notion, and Google Sheets, with async updates via Slack. If you have an existing format or schema, send it before the intake call and we will match it.
How quickly can you onboard a new project?
A 30-minute intake call produces a task spec document within 24 hours. The annotator team is briefed the same day. The pilot batch is typically returned within 48 to 72 hours of sign-off on the spec. For Scale retainer clients, onboarding includes custom rubric development which adds one to two working days before the first delivery.
Get in touch
Tell us what you are annotating and how many tasks you need. We will scope it on a call and have a pilot batch back to you within 48–72 hours, founder-reviewed before delivery.
No retainer required to start. Pilot Sprint available from £400.