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Dwija Technolabs

AI engineering partner

AI that ships.

We turn your business problem into a working AI product (agents, copilots and automation) in weeks, not quarters.

  1. Scattered tools.
  2. We connect it.
  3. We make it understand.
  4. And ship it.
  5. Built with you.
building production AI systems
Since 2023
to a working prototype
2 weeks

AI is everywhere. Results aren't.

“We don't know where to start.”

There are dozens of tools and no clear path to ROI.

“Our pilot never reached production.”

The demo impressed everyone. Then real data, security and scale broke it.

“Off-the-shelf tools don't fit.”

Your workflows are specific. Generic chatbots aren't.

What we build

From first idea to AI in production

Custom AI development for businesses that want results, not experiments.

AI Strategy & Roadmap

Find the two or three AI use cases with the highest return for your business, and a plan to deliver them.

Custom AI Agents

Agents that do real work: triage tickets, process documents, and update the systems you already use.

LLM Apps & Copilots

Assistants that answer accurately from your own documents and data, with sources cited.

AI Product Engineering

Full product builds, from MVP to scale, held to enterprise engineering standards.

Data & ML Engineering

Pipelines, analytics and forecasting models: the foundation every AI project needs.

AI Integration

Bring AI into your CRM, ERP and internal tools without replacing them.

Proof

Built for production, not for demos

Systems our team has engineered, and AI demos you can try yourself.

Domain expertise · Enterprise automation

Agentic workflow automation at enterprise scale

Problem
Enterprises needed to automate IT operations across complex, distributed infrastructure.
What was built
Workflow execution services, data ingestion and analytics pipelines on Kubernetes.

Built for enterprise scale

Domain expertise · Device orchestration

Reliable delivery to thousands of devices

Problem
Legacy templates made configuration rollouts fragile and hard to audit.
What was built
A distributed, event-driven deployment system with retries, rollback and a real-time dashboard.

Fault-tolerant by design

Live demo · Coming soon

Chat with your company's documents

Problem
Staff spend hours searching policies, manuals and past tickets.
What was built
An assistant over your knowledge base that cites its sources and respects permissions.

Try it on this site

Why Dwija

Enterprise engineering. Agency speed. Clear accountability.

Built at scale before

Hands-on experience shipping agentic AI and workflow automation on enterprise platforms.

Production-first

Security, evaluations, monitoring and cost control are built in from day one.

You own everything

Your code, your data, your IP. No lock-in.

How we work

A clear path from idea to impact

  1. 1

    Intro call

    30 minutes. You tell us what you're building, we capture the requirements and set up the project repo.

    No obligation

  2. 2

    Prototype sprint

    A working prototype on your real data.

    About 2 weeks · fixed price

  3. 3

    Production build

    Hardened, integrated, tested and deployed.

    Milestone-based

  4. 4

    Optimize & scale

    Monitor, improve accuracy and lower running costs.

    Optional retainer

Frequently asked questions

How much does a custom AI solution cost?

It depends on scope. Most engagements start with a fixed-price prototype sprint so you see working software before committing to a full build. Cost is driven by the number of systems to integrate, data preparation, and accuracy and security requirements. We give you a clear estimate after our first conversation.

How long does it take to build?

A working prototype typically takes about two weeks. A production-ready system usually takes six to twelve weeks, depending on integrations and scope.

Is our data safe? Where is it stored?

Your data stays yours. We design for PIPEDA compliance, can host in Canadian data centres on request, and use AI providers and settings that do not train models on your data.

Do we need a lot of data to use AI?

Often, no. Modern language models can work with the documents, emails and records you already have. We assess what you have during our first conversation and tell you honestly what is possible.

Tell us what you're building.

Start with a relaxed 30-minute conversation. We'll listen, capture your requirements and, if it's a good fit, set up the project repo so work can begin.