Technology
Tools chosen for the job,not for the brochure.
We work across the major annotation platforms and build our own automation and AI tooling in Python and React. The stack for any project is picked to fit its workflow and constraints.
The stack behind the work
Tools and technologies our team works with. Not every technology is used on every project — the stack is chosen to fit the workflow.
- Python
- React
- FastAPI
- SQLite
- Git
- Google Apps Script
- Google Workspace
- LLMs
- RAG
- Prompt Engineering
- Pinecone
- Computer Vision
- NLP
- OCR
- CVAT
- Label Studio
- Labelbox
- SuperAnnotate
- Encord
- Ango Hub
- Dataloop
Engineering
- Python
- React
- FastAPI
- SQLite
- Git
AI
- LLMs
- RAG
- Prompt Engineering
- Pinecone
- Computer Vision
- NLP
- OCR
Automation
- Google Apps Script
- Google Workspace
Annotation platforms
- CVAT
- Label Studio
- Labelbox
- SuperAnnotate
- Encord
- Ango Hub
- Dataloop
Quality is not the final step.It is built into the pipeline.
Errors are expected in any annotation workflow. What matters is how quickly they are detected, explained and prevented from recurring.
- 01
Annotation
pass path
- 02
Automated checks
pass path
- 03
Human review
pass path
- 04
Error detection
issue path
- 05
Root-cause analysis
issue path
- 06
Correction
issue path
- 07
Final validation
pass path
- 08
Delivery
pass path
Detected
flagged in review
Explained
root cause recorded
Prevented
guideline updated
Ready to turn your datainto AI-ready intelligence?
Tell us what you're building. We'll help you design the data workflow behind it.
iamayyubansari@gmail.com