A spin-off of Rise Research
Expert Data for AI, Built on the Rise Research PhD Mentor Network
Our experts work on bleeding-edge research and sit at the very pinnacle of their fields. The same academics who mentor Rise Research students now create post-training data for AI teams: RL preference data, reasoning traces, and evaluations. Fast to start, and ready to scale to thousands.
Math · Mathematica
Engineering · MATLAB
Code · Python
SAMPLE TASK · MATH · PREFERENCE
Expert reviewing
PhD
Expert: PhD, Mathematics
Verified · Analysis & PDEs
Evaluate ∫₀^∞ sin(x) ⁄ x dx
A
The integral diverges, because |sin(x) ⁄ x| is not integrable on [0, ∞).
B
It converges to π ⁄ 2. This is the Dirichlet integral, which converges conditionally.
Wolfram Mathematica · check
In[1]:=
Integrate[Sin[x]/x, {x, 0, Infinity}]
Out[1]=
π/2
EXPERT RATIONALE
A confuses absolute and conditional convergence. The integral is not absolutely convergent, but it does converge. B is correct and names the result.
Gold task · matches key
No paste events
Built on Rise Research
We didn’t recruit a crowd.
We already work with them.
Rise Research Data Labs is a spin-off of Rise Research. Every expert comes from the academic network that already mentors Rise students: researchers working at the frontier of their fields. We know how they work long before they touch your data.
100,000+
academic experts worldwide
10,000+
PhDs from top-20 universities
Proven before day one
Most vendors screen strangers. We have a working history with each mentor: their reliability, rigor, and communication.
Trained to explain reasoning
Mentors spend their time showing students why an answer is right. That is exactly what strong rationales and reasoning traces need.
Accountable over time
Our experts have an ongoing relationship with Rise. Cutting corners on your project puts their mentoring work at risk too.
Speed and scale
Quick to start. Built to scale.
Because our experts are already vetted and working with Rise, we skip the months most vendors spend recruiting. Scaling is a non-issue for us: we have a strong operations team in place that is built to run projects at this size.
48 hours
Matched expert shortlist
Tell us the domain and task. We send profiles of matched experts from our existing network.
1 week
Pilot delivering data
A small team completes calibration and delivers a first batch you can review.
1,000s in a week
Experts when you need them
Scale from 10 experts to thousands within a week, with the same reviewers and gold tasks, so quality holds as volume grows. We will plan the exact ramp with you on a call, based on your budget.
Mathematics
Physics
Computer science & coding
Medicine
Biology & life sciences
Chemistry
Law
Finance
Economics
Ask about your field
What we deliver
The data RL and eval teams actually need
RLHF · DPO
Preference ranking
Experts compare model responses, pick the better one, and explain why.
SFT
Expert demonstrations
Ideal answers written from scratch by specialists in the field.
REASONING
Reasoning traces
Step-by-step solutions and step-level grading that finds where a model goes wrong.
EVALS
Rubrics and benchmarks
Hard questions current models fail, with clear grading rubrics.
How we vet experts
Rise track record first, then a five-stage screen
Credentials and Rise history
Degree and ID verified, and Rise mentoring record reviewed.
Domain test
Timed PhD-level problems, including questions AI models get wrong.
Paid trial
Real annotation work: ranking responses, finding errors, writing rubrics.
Live interview
A short video call where experts walk through their own answers.
Probation
First tasks double-reviewed and scored against hidden gold tasks.
Quality and integrity
Built to catch pasted AI answers
Hidden gold tasks with known answers, mixed into every expert’s work.
AI traps: questions where models give a known wrong answer.
Paste logging and time tracking on every task.
Senior review of at least 15% of tasks.
For larger programs
Offline proctored networks
For frontier labs and large contracts, we are open to setting up offline proctoring networks: supervised in-person centers where experts work on locked-down machines with no access to ChatGPT or other AI tools. Scope and terms are agreed per contract.
Discuss a proctored program
Our guarantee
You pay for accepted work only.
acceptance rate = tasks you approve ÷ tasks we deliver
0%
90% credit line
95% target
Rejected tasks are credited back. If an expert is caught using AI, we audit everything they submitted and credit back any bad work.
FAQs
All
Experts
Quality
Speed & scale
Working together
How is Rise Research Data Labs related to Rise Research?
How do you vet your experts?
Which fields and tasks can you cover?
How do you stop experts from using ChatGPT or other AI tools?
What happens if the data isn't good enough?
Can you run offline, proctored work for large programs?
How do you measure quality?
How quickly can you start?
How fast can you scale?
Do you work in our annotation tool?
How do you keep our data confidential?
How does pricing work?
Book a call
Tell us the task your model struggles with most.
Pick a time that works for you, or email us your domain, task type, and timeline. We reply with a matched expert shortlist and a pilot plan.
Rise Research Data Labs
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