AI data labeling
Image, video, text and audio annotation to your taxonomy, from bounding boxes and polygons to NER spans and intent tags.
Data talent for AI teams
Surge-ready data talent, on demand.
Chrysolite Solutions supplies trained specialists for data labeling, model training, data QA, extraction and analysis. We staff your short-term spikes so releases ship on time and the data holds up to review.
0htarget time to first trained team
0from first call to full production
0QA on every deliverable
Sample data, for illustrationitems labeled 0
What we supply
Specialists for every stage of the data pipeline.
Each team is matched to your task, trained on your guidelines and run by a Chrysolite lead who owns throughput and quality.
Model training support
RLHF preference ranking, supervised fine-tuning data, prompt and response writing, and red-team conversations by domain-qualified writers.
Data QA
Independent review of existing datasets or vendor output. We audit samples, score against gold sets and send back corrected labels with error reports.
Data extraction
Structured fields pulled from contracts, invoices, filings, product pages and scanned forms, normalized to your schema and validated.
Data analysis
Analysts who clean, join and profile your data, track label distributions and drift, and report findings your ML team can act on.
Managed surge teams
A complete pod with annotators, reviewers and a project lead that plugs into your tools and ramps up or down by the week.
The surge model
Your core team handles the baseline. We cover the spikes.
Model launches, new data sources and customer escalations create short peaks of work. Hiring for the peak leaves people idle afterward. Chrysolite fills the gap and steps back when volume returns to normal.
task volumein-house capacitycovered by Chrysoliteillustrative
Fast ramp
A pre-vetted bench means a matched, trained team in days. No recruiting cycle on your side.
Elastic headcount
Add or release seats week to week as the queue changes. You pay for the work in front of you.
Clean exit
When the surge ends we hand back guidelines, edge-case logs and final QA reports, so your team keeps the knowledge.
How an engagement runs
From first call to delivered data.
A typical surge project follows these five steps. Timelines below are targets for a standard labeling or QA task.
1
WEEK 1
Scope
We review your guidelines, sample data, volume and deadline, then confirm team size and quality targets.
2
WEEK 1
Match
Specialists with the right domain and tool experience are selected from our bench.
3
WEEKS 1–2
Calibrate
A pilot batch is scored against your gold set. Guidelines are tightened until agreement meets target.
4
WEEK 3
Testing
A test batch runs at production pace. We confirm throughput, accuracy and reporting with you before full volume.
5
WEEK 4
Project start
Full production begins with daily throughput and quality reports. Seats scale with the queue, and your data and IP stay yours.
Quality you can measure
Speed only matters if the labels are right.
Every project gets agreed quality targets before production starts. These are the default targets we propose; we adjust them to your task.
Label accuracy vs. gold set≥ 98%
Scored on hidden gold items mixed into every batch.Inter-annotator agreementκ ≥ 0.85
Cohen's or Fleiss' kappa on overlapping items.Reviewed by a second specialist100%
Each item passes a reviewer before delivery.Senior audit sample10%
Random sample checked by the project lead each day.LAYER 1
Annotator self-check
Built-in validation rules and guideline checklists catch errors at the source.
LAYER 2
Peer review & consensus
A second specialist reviews every item. Disagreements go to adjudication, not a coin toss.
LAYER 3
Lead audit & gold scoring
Daily audits and gold-set scores feed a quality report you can read before accepting a batch.
ALWAYS
Secure handling
NDAs for every specialist, work inside your tools or ours, access removed on project close.
Analytics in motion
We don't just label data. We read it.
Our analysts profile every dataset as it moves: clustering, drift, anomalies and label balance, reported while the project runs. The panels below use simulated data to show what that looks like.
Simulated
Clustering · k-means on embeddings
cluster Acluster Bcluster Ccluster Diteration 0
Simulated
Label balance
Simulated
Anomalies flagged
0items
Simulated
Distribution drift · live vs. training set
0.00PSI
training setincoming data
Engagement models
Pick the shape of support you need.
All engagements are short-term by design. Pricing is quoted per project once we know the task, volume and deadline.
1–3 months
Surge Sprint
For a single deadline: a launch, a backlog or an urgent relabel.
- Team of 5–50 specialists
- Pilot batch before production
- Daily throughput report
3 months +
Project Pod
For a defined program with changing volume, run end to end by a Chrysolite lead.
- Dedicated project lead & reviewers
- Weekly seat scaling
- Three-layer QA with gold-set scoring
- Final documentation & hand-back
On call
Standby Bench
For teams that know spikes are coming but not exactly when.
- Pre-trained on your guidelines
- Activate within days
- Pay only for active weeks
Questions
Common questions
Anything else, ask us in the form below.
How short can an engagement be?
A Surge Sprint runs 1 to 3 months. Scoping and team matching take the first week, calibration runs into week 2, a test batch runs in week 3 and full production starts in week 4. Longer programs run as a Project Pod of 3 months or more. For smaller QA audits we can scope a fixed-size review that finishes sooner.
Do you work in our labeling tools?
Yes. Our specialists work in your platform of choice, whether that's an in-house tool or a commercial annotation platform. If you don't have one, we can set up a workspace for the project.
How do you keep quality high when scaling quickly?
Every new specialist passes a calibration batch scored against your gold set before touching production data. Peer review, consensus and daily lead audits continue for the life of the project.
Who owns the data and the labels?
You do. All data, labels, guidelines and derived work belong to you. Specialists sign NDAs, and access is revoked when the project closes.
Can you handle specialist domains?
We match specialists by domain for work that needs it, such as finance, legal, healthcare, code and multilingual tasks. Tell us the domain when you request a team.
Start a project
Have a spike coming? Let's staff it.
Tell us about the task, the volume and the deadline. We'll come back with a team plan and a quote.
Team plan within one business day
Paid pilot batch before you commit
NDA available before you share data