Services/Deep learning

Capability

Deep learning

Perception models when off-the-shelf is not enough.

Vision, speech, and document models trained or adapted to your domain, then deployed with evaluation and ops in mind.

What we build

The engineering pieces included under this capability.

01

Computer vision

Detection, inspection, OCR, and visual classification.

02

Document AI

Extract structure from messy forms, invoices, and scans.

03

Speech / audio

Transcription and signal tasks where domain accuracy matters.

04

Adaptation

Fine-tune or train on your labelled data when generics fail.

05

Evaluation

Holdout sets, error analysis, and production quality bars.

Example use cases

Concrete jobs this capability is built for. Not a full project proposal.

01

Visual inspection / QA

Detect defects or missing parts in product images or line video so humans only review the exceptions.

02

Document intake

Read invoices, forms, or IDs, pull the fields you need, and write them into your system of record.

03

Domain-specific text tasks

Classify or extract meaning from industry language where a generic model misses the nuance.

Build path

  1. 01

    Data & labels

    What exists, what quality, what is missing.

  2. 02

    Model choice

    Reuse, adapt, or train; pick by accuracy and cost.

  3. 03

    Deploy

    Serve predictions with monitoring and a retrain path.

Typical stack

Training

PyTorchKerastransfer learning

Vision / speech

YOLO-familyOCR stacksASR as needed

Serving

PythonGPU or CPU inferenceFastAPI

Need this in production?

Bring the use case and constraints. We will say if a sprint or pilot fits.

Book a 2-week architecture sprint