Data annotation for AI teams
Training data your models can trust.
Expert annotators and purpose-built tooling for LiDAR, image, video, text and generative AI data, backed by a 98%+ accuracy guarantee.
- 100M+ annotations
- 200+ projects
- 23 countries
Trusted by 50+ AI teams, from startups to enterprises
- Annotations delivered
- 100M+Annotations delivered
- Projects completed
- 200+Projects completed
- Countries served
- 23Countries served
- AI teams supported
- 50+AI teams supported
What we label
Every modality your model learns from
One partner for perception, language and generative AI data, each handled by a team trained on that modality.
3D point cloud & LiDAR
Perception data for autonomous vehicles and robots, labeled in 3D and synced across camera and LiDAR frames.
- 3D cuboids
- Point-level semantic segmentation
- Lane and polyline marking
- Polygon annotation
- 2D boxes on synced camera frames
Services
Everything between raw data and a trained model
Bring us a dataset, a guideline or just a goal. We supply the people, the process and the tooling.
Data annotation
Managed annotation teams for LiDAR, image, video, text and audio, trained on your guidelines.
Learn moreGenerative AI & RLHF
Preference ranking, evaluations and prompt–response data to align LLMs and LVMs.
Learn moreData collection
Custom image, video, audio and text datasets when the data you need doesn't exist yet.
Learn moreData curation & QA
Cleansing, de-biasing and validation of existing datasets before they reach training.
Learn more
Our platform
Purpose-built tooling for managed projects
Our teams work in our own annotation platform at app.intellisane.ai, built for managed annotation projects. You can use it directly, too.
- Batches & assignmentSplit projects into batches and assign them across annotators.
- Review workflowReviewers approve or reject with comments, batch by batch.
- Progress & usageTrack status per asset and batch, and usage against plan limits.
- ExportCOCO JSON, YOLO, Pascal VOC or custom JSON.
How we work
A process built around your feedback
We calibrate on a pilot before scaling, so the labels you receive at volume match what you approved at the start.
- Step 01
Consult
We review your data, edge cases and success criteria, then write annotation guidelines with you.
- Step 02
Annotate
A trained team labels a pilot batch, following the agreed guidelines to the letter.
- Step 03
Calibrate
You review the pilot. We fold your feedback into the guidelines before scaling up.
- Step 04
Multi-layer QA
Every batch passes peer review, expert QA and automated checks before it leaves us.
- Step 05
Deliver
Labels ship in your format on your schedule, ready to drop into training.
Quality pipeline
Five checkpoints between raw data and your model
- 01AnnotatorLabels against your guidelines
- 02Peer reviewA second annotator reviews the work
- 03Expert QASenior reviewer samples and corrects
- 04Automated checksRules catch missing or invalid labels
- 05Client sign-offYou approve before final delivery
Industries
Domain teams for the problems you're solving
Annotators trained on your industry's edge cases, not just the tool.
Autonomous & ADAS
Perception data for vehicles and mobility
Manufacturing & Robotics
Inspection, picking and navigation data
Medical & Healthcare
Radiology, pathology and dental labeling
Agriculture
Crop, livestock and field-mapping data
Retail & E-commerce
Product, shelf and checkout vision data
Sports Analytics
Player, ball and pose tracking
Security & Surveillance
Detection, tracking and OCR for safety
- Talk to our team
Don't see your industry?
We build guidelines and teams around new domains. Tell us what your model needs to learn.
Case studies
Results our clients shipped
Agriculture
Sugarcane plant annotation at scale
Drone imagery labeled plant by plant with custom tooling, giving the client's crop model dense, high-accuracy training data.
- Plants annotated
- 4.8M
- Plants annotated
- Row-alignment lines
- 1.2M+
- Row-alignment lines
Sports Analytics
Volleyball player and ball tracking
Fast-moving players and the ball tracked across high-intensity match footage for a sports-tech analytics product.
- Annotation accuracy
- 98.7%
- Annotation accuracy
- Bounding boxes
- 100K+
- Bounding boxes
Testimonials
What our clients say
“Intellisane AI played a key role in helping us reach 97% accuracy in automating foundation layout detection. Their deep understanding of spatial data and labeling precision brought measurable improvements to our AI pipeline. The team was communicative, detail-oriented, and delivered everything ahead of schedule.”
S. RagavanSr. ML Engineer, Taranto
“Our fashion AI model required pixel-level segmentation across 72 garment categories, and Intellisane AI handled it flawlessly. They quickly adapted to our complex annotation guidelines and delivered consistent, high-quality labels at scale. Their domain focus, speed, and attention to visual detail were exactly what we needed.”
Valerio ColamatteoSr. AI Scientist & Team Lead, MindEarth
“For our ADAS project, Intellisane AI delivered precise vehicle annotations across diverse traffic scenes, including multiple object classes and occlusion scenarios. Their expertise in automotive data workflows and quality-first mindset helped us pass all validation checks, with timely delivery and professional communication throughout.”
Raphael LopezCo-Founder & CTO, Felucca
Our people
The people behind your data
Annotators, reviewers and project leads working together from our offices in Bangladesh, trained on each client's guidelines before they label a single item.
- Accuracy guarantee
- 98%+Accuracy guarantee
- Returning clients
- 96%Returning clients
- Cost reduction
- 2.5xCost reduction
- Model efficiency
- ~99%Model efficiency
- Pilot to millionsStart with a small batch, then scale the same team as volume grows.
- Your data stays yoursStrict data-privacy protocols and secure infrastructure at every step.
- Startup to enterprisePricing that fits a proof of concept as well as a production pipeline.
Global presence
From early-stage startups to established enterprises, AI teams in 23 countries rely on us for production training data.
Start with a pilot
Label your training data with a team that gets it right
Send us a sample. We'll annotate a free pilot batch to your guidelines so you can judge the quality before you commit.