Service
Computer Vision & Natural Language Processing
Give your systems the ability to read documents, understand text at scale, and turn unstructured data into usable output in production.
Discuss Your ChallengeComputer Vision & NLP Solutions
Computer vision and NLP often deliver some of the fastest returns in enterprise AI because they replace work that is manual, repetitive, and prone to error. Teams use them to process documents, inspect products, analyse contracts, and classify customer communication at scale. Katalyst AI Lab has built vision and NLP systems for manufacturing, healthcare, publishing, and legal environments.
Computer Vision
Vision Services
| Service | Description | Example Output |
|---|---|---|
| Object Detection & Classification | Real-time detection using YOLO v8/v9 for manufacturing QA, security, retail analytics, and logistics. | Bounding boxes, class labels, confidence scores, streamed or batched |
| Document Understanding & OCR | Structured data extraction from PDFs, scanned forms, invoices, contracts, and medical records including tables and complex layouts. | JSON output: extracted fields, table data, key-value pairs, section boundaries |
| Medical & Satellite Imaging | Radiology image analysis, pathology slide processing, and satellite imagery interpretation for life sciences and geospatial applications. | Anomaly masks, region-of-interest coordinates, classification with confidence |
| Visual Inspection (Manufacturing) | Defect detection on production lines using industrial cameras. Sub-millimetre accuracy at production speeds. | Pass/Fail + defect type + pixel-level mask |
| Video Analytics | Real-time or batch processing of video feeds for event detection, activity recognition, and anonymised behavioural analytics. | Event timestamps, object tracks, activity classification per clip |
NLP
NLP Services
| Service | Description | Example Output |
|---|---|---|
| Information Extraction | NER, relation extraction, and event detection from contracts, research papers, clinical notes, and news feeds. | Structured JSON: entities, types, relations, confidence; linked to source offsets |
| Document Classification | High-accuracy classification of documents, emails, support tickets, or regulatory filings at enterprise scale. | Category label + confidence + multi-label when applicable |
| Sentiment & Intent Analysis | Customer feedback analysis, complaint triage, voice-of-customer programmes, and call centre transcript analysis. | Sentiment score, intent class, urgency signal, suggested routing |
| Clinical NLP | ICD coding assistance, clinical text de-identification (HIPAA/GDPR), drug-drug interaction extraction, clinical trial recruitment screening. | Structured FHIR-compatible output; coded concepts with source spans |
| Multilingual NLP | NLP systems covering Indian languages (Hindi, Tamil, Bengali, Marathi), European languages, and Arabic. | Same structured outputs as above, per-language model or multilingual model |
FAQ
Questions
How accurate are computer vision systems?
Accuracy depends on the quality of the training data and the complexity of the task. In controlled settings such as manufacturing lines or standard document formats, well-trained models often reach 97 to 99 percent accuracy. For more variable inputs, performance is usually lower, which is why we benchmark on your actual data before production decisions are made.
Can you handle Indian regional languages?
We have built pipelines for Hindi, Tamil, Telugu, Bengali, and Marathi. Final accuracy depends on the training data available for the target language, and we assess that during discovery.
How do you handle GDPR / HIPAA compliance?
For regulated document workflows, we build de-identification pipelines as a preprocessing step before model training or inference. Processing can be configured to stay within your approved cloud environment and data residency boundaries.
What Data Are You Still Processing Manually?
Describe your vision or NLP challenge. We'll scope a production-ready solution. No commitment required.
Discuss Your Vision or NLP Challenge