Services

Three services. Real depth in each.

Enterprise AI, Computer Vision, and Application Engineering — chosen because they compound. AI needs software to run in. Software needs intelligence to differentiate. We build both.

ENTERPRISE AI

When your data is already there — and you need it to do something.

Most enterprise AI projects fail not because of model quality but because they were built in isolation from the systems that hold the actual data. Codemonk builds AI that runs inside your existing infrastructure — reading documents, interpreting telemetry, processing contracts — without requiring you to change how your data is stored or accessed.

Document Intelligence

Extract obligations, decisions, and clauses from unstructured contracts, claims, and tenders.

Predictive Anomaly Detection

Flag system failures before they cascade using sensor telemetry and historical pattern models.

RAG Systems

Query any corpus — contracts, manuals, incident logs — in plain English via production-grade retrieval pipelines.

GenAI Integrations

Embed LLM-powered workflows into existing operations tools without replacing them.

Claims & Policy AI

Read multi-document submissions together and surface decision-ready summaries.

Tech stack
AWS BedrockOpenAI APILangChainPineconePostgreSQL + pgvectorPythonFastAPI
Minutes
to review a multi-party contract — obligations extracted, deviations flagged
10,000 docs
queryable in plain English with source citations, for an engineering firm in Japan
Best fit if you have

Large volumes of unstructured documents. Sensor or telemetry data generating alerts you can't action fast enough. An existing operations stack you can't afford to replace. A need to surface intelligence from data your team already has.

COMPUTER VISION & INDUSTRIAL AI

Machines that see — deployed where the work actually happens.

Computer vision that runs on a phone on the shop floor, on a drone above a construction site, or on an edge device in a packaging line — not in a cloud demo. Codemonk builds vision systems designed for the physical constraints of industrial environments: variable lighting, no reliable connectivity, sub-second inference requirements.

Shelf & Retail Intelligence

Audit store shelves from a single phone photo — SKUs, facings, gaps, and pricing.

Aerial Reconstruction

Turn raw drone footage into surveyable 3D models and site-monitoring dashboards.

Automated Visual Inspection

Replace manual shift-by-shift checks with vision systems running at line speed.

Edge Deployment

Run inference on-device with no cloud dependency — FMCG lines, warehouses, remote sites.

Workplace Safety (VisionOS)

Real-time PPE compliance and hazard detection deployed across industrial facilities.

On-device
Inference on the hardware that's already there

Sub-second results, no round trip. Keeps working when the line loses signal.

Cloud round-trip
What most vision demos assume

Fine in a browser tab. Breaks down on a factory floor or a site with patchy connectivity.

Tech stack
YOLODeepSORTOpenCVTensorRTONNXPyTorchRaspberry Pi / Jetson EdgeAWS IoT Greengrass
Our own product

VisionOS — our own computer-vision platform for industrial safety and operations, running in production across construction sites and manufacturing facilities.

Learn more about VisionOS

APPLICATION ENGINEERING

When the product exists — and it needs to scale, perform, or actually ship.

Not every engagement starts with a blank canvas. Codemonk takes on platforms mid-journey — re-architecting runtimes for enterprise load, rebuilding operations workflows that outgrew the spreadsheet, or redesigning products that work but frustrate. Engineers who can read an existing codebase critically and improve it without burning it down.

Platform Re-architecture

Carry existing systems through enterprise scale without losing developer experience.

Operations Platforms

Replace spreadsheet-driven workflows with purpose-built systems across field operations, supply chain, and logistics.

Product Redesign & Engineering

Research-led redesign of dense, complex products into flows that feel obvious.

Mobile & Web Development

Full-stack build from design system through to production deployment.

CI/CD & Infrastructure

Engineering the delivery pipeline alongside the product.

Tech stack
ReactReact NativeNode.jsTypeScriptPostgreSQLAWSDockerKubernetesFigma

How we engage

How a project actually runs.

From first conversation to production deployment. No waterfall. No 12-week discovery before a line of code is written.

1
Week 1–2

Scoping

A structured conversation about what you're building, what currently exists, and what success looks like. We'll challenge assumptions where we see risk. Output: a written scope with delivery milestones and an honest assessment of what we don't know yet.

2
Week 2–4

Proof of Architecture

For AI and CV engagements, we build a working prototype on your actual data before committing to full delivery. For application engineering, we audit the existing codebase and produce an architecture recommendation. This is where we de-risk the engagement — for both sides.

3
Weeks 4–N

Iterative Delivery

Two-week sprints with a demo at the end of each. Production deployments happen incrementally — not in a big-bang release at the end of the contract. You see working software throughout, not at the end.

4
Ongoing

Production & Handover

We deploy. We document. If you have an internal team taking over, we run a structured handover with them. We don't disappear at go-live.

We don't start a full engagement without validating the architecture on your data first. It protects you from a six-month build that solves the wrong problem.

Every project has a named technical lead from Codemonk — not a rotating cast of contractors.

Project-based

Defined scope, fixed milestones, clear ownership.

Best for: New product builds and defined platform upgrades.

Embedded team

Codemonk engineers work as an extension of your in-house team.

Best for: Ongoing platform development or scaling engineering capacity.

AI advisory

Architecture review, proof-of-concept build, and a technical roadmap.

Best for: A starting point for enterprise buyers evaluating AI adoption.

FAQ

Questions that usually come up on a first call.

Scaling an existing platform or building something new with AI? Let's talk.

Tell us what you're building. You'll hear from our team — usually within a working day.

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