Image data
Photos captured or sourced to your scenarios, devices, lighting and demographics.
Data collection for AI training
Custom data collection across text, image, audio and video, fueling high-performance AI models from the ground up.
- Image · video · audio · text
- Ethically sourced
- Collected to your distribution
collection_brief_v2.pdfannotation
Image
Speech
Medical
Manufacturing
Dental
Agriculture
Documents
Retailillustrative examplesample data
What we collect
The data you need, when it doesn't exist yet
We source, generate and curate datasets tailored to your use case. From real-world images to multilingual speech and domain-specific text, you get accurate, diverse and ethically sourced data.
Video data
Footage of the actions, environments and edge cases your model must handle.
Speech & audio
Scripted and spontaneous speech across speakers, accents, languages and noise conditions.
Text & documents
Handwriting, forms, receipts and domain-specific text, from conversational data to documents.
Medical imaging
De-identified scans and clinical photos collected with consent and privacy safeguards.
Dental data
Intraoral photos, impressions and radiographs collected with partner clinics.
Manufacturing
Production-line, inspection and robot-cell imagery across shifts, products and defect types.
Retail
Shelves, products and store scenes across chains, layouts and lighting.
Agriculture
Field, crop and livestock imagery across seasons, growth stages and weather.
Conversational data
Multi-speaker dialogues and chats on the topics and in the languages you need.
Coverage tracking
Collected to your brief, not whatever is easy
We plan collection around the scenes, conditions and devices your model will actually see, then track coverage until every cell of the brief is filled.
- Scenario and condition matrix agreed up front
- Consent and privacy handled at capture
- Metadata: device, location type, lighting
Coverage vs. collection brief · illustrative
UrbanHighwayRuralRetail
Daylight
✓
✓
92%
✓
Night
✓
84%
70%
88%
Rain
88%
76%
62%
n/a
Indoor
n/a
n/a
n/a
96%
urban
highway
rural
retail
night
transitUse cases
Where teams put this data to work
Filling edge cases
Night, rain, rare objects and unusual angles your current dataset lacks.
New markets & languages
Speech and text from new regions, accents and dialects.
Product launches
Images of new SKUs or devices before real-world data exists.
Benchmark sets
Purpose-built, balanced test data for fair model evaluation.
How we work
From pilot to production
We start with your data needs and target distribution, deploy the right collection methods, from controlled environments to real-world sourcing, and check quality at every stage. You get curated, structured data ready for your pipeline.
- 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
98%+
Accuracy guarantee
- 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
Results
Quality you can measure
- Accuracy guarantee
- 98%+Accuracy guarantee
- Returning clients
- 96%Returning clients
- Cost reduction
- 2.5xCost reduction
- Projects completed
- 200+Projects completed
“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 Lopez
Co-Founder & CTO, Felucca
Related
Supplying training data for autonomous vehicles, robotics, fintech, healthcare, voice assistants, legal AI and beyond.
FAQ
Questions, answered
Something else on your mind? Email sales@intellisane.ai.
Get started
Let's scope your project
Tell us about your data. We'll come back with a plan and a free pilot batch so you can see the quality first.