Agree the requirements
Define the task, output format, acceptance checks and delivery schedule.
AI training data / Benchmarking / Expert teams
Build the tasks.
Test the models.
Check the work.
We build coding tasks, benchmark datasets and evaluation workflows with engineers, ML specialists and domain experts. From SFT and RLHF data to agent environments and technical QA, we help teams turn project requirements into work they can inspect.
Clorvin Labs Pvt Ltd / India
Data. Evaluation. Expertise.
01 /What we do
Technical teams.
Clearly defined work.
From a single task format to an ongoing programme, we agree on the output and the checks before getting started.
01020304
Software engineering & coding tasks
Debugging, repository changes, build issues and test failures. Clear task instructions, reference solutions and checks for the expected result.
AI benchmarking & evaluation
Tasks that test the work a model needs to do. We define scoring criteria, review responses and document where a solution falls short.
Docker & terminal environments
Reproducible environments for coding and agent tasks. We check dependencies, terminal workflows and the verifiers that judge the result.
Technical review & quality assurance
Independent checks on instructions, code and evaluation results. Issues are recorded, corrections are reviewed and acceptance is documented.
02 /Task Library
The work.
With the files behind it.
Explore 100+ samples across 9 categories. Read the task, inspect the environment and follow the verification code. Browse terminal tasks and original examples of dataset QA, scoring and ML workflows.
Open the task libraryClorvin Originals / Task collectionAlso see our executed internal examples
03 /How we work
Quality is part
of the delivery.
Instructions, environments and tests need review too. We check the task as well as the solution.
Build and review
Assign the work to the right engineers and arrange an independent review.
Check the corrections
Record issues, resolve them and run the agreed checks again.
Deliver with context
Hand over the work with review notes and a named point of contact.
04 /Careers
Work on the problems
you know.
Have 2+ years of experience? Join our project network for coding, AI evaluation, dataset review and specialist work. Tell us where your experience fits.
Explore careersSoftware engineer
Build coding tasks, repair repositories and write reference solutions.
Tell us about your workML & evaluation specialist
Design evaluation cases and check model outputs against a clear rubric.
Tell us about your workDomain expert
Bring subject knowledge to tasks where technical correctness needs specialist review.
Tell us about your workWhat projects can you support?
Coding task development, software engineering, AI benchmarking, agent evaluation, Docker environments and technical QA. If your project is different, send us the scope and we’ll tell you whether we can help.
Can you work with our platform and guidelines?
Yes. We can work within your task format, tools and review process. We agree on access, acceptance criteria and responsibilities before work begins.
How do you decide team size?
We look at task complexity, review requirements, expected volume and contributor availability. We confirm a delivery team for the project rather than treating the wider network as immediately available capacity.
How do you handle corrections?
We record the issue, return it to the right person and review the correction against the original requirements. The delivery record shows what changed and what was accepted.
Do we have to start with a trial?
No. We can discuss a defined project or ongoing delivery support. The scope, quality checks and schedule are agreed before work starts.
Work with Clorvin
Tell us what needs doing.
Share the scope, the expected volume and your timeline.
We’ll work out where our team can help.