Custom software & app development

Any app. Any system. AI + experts.

SaaS and MVP development, AI-built app completion, white label development for agencies, and business integrations, guided by experienced engineers from design and testing to launch.

What we do

Every discipline.
One accountable team.

Design, engineering, QA and DevOps in one team, so nothing falls between vendors. AI speeds up every discipline; experienced specialists direct the work, check the results and stay accountable for them.

Every project

We use AI to build software

AI tools speed up design, engineering, QA and operations, whatever you're building. Your product doesn't need an AI feature to benefit.

Compare development packages

When your product needs it

We build AI into software

AI agents, LLM features, chatbots and models inside your product, with permissions, evaluation and human oversight designed in. A separate service.

Explore AI agents & automation

Also availableSEO & Digital GrowthTechnical SEO, content, paid campaigns and analytics, for new and existing clients who need them.

One team across the software lifecycle

Explore our software development, QA, DevOps, UI/UX and integration services, with two AI delivery options. These figures describe the current service catalogue.

  • 2AI Delivery Options
  • 4Core capabilities
  • 39Specialist services
  • 13Platform integrations

AI delivery options

Two ways to build.
One engineering standard.

Both packages deliver the same expert-led, AI-assisted engineering. They differ in where AI tools process your code and project context while we build, and in what has to be set up and run.

  • For controlled environments

    Private / Local AI Engineering

    Privately hosted models

    Software delivery with suitable privately hosted models, inside a processing environment we agree with you. It's an engineering engagement, not GPU rental: we select and evaluate models, set up development agents and their permissions, and deliver with the same expert design, QA and release control.

    Best fit

    Policies that keep source code, prompts and research inside a boundary you control.

    AI processing environment
    Open-weight models on your infrastructure or in an agreed isolated environment.
    Setup
    Model evaluation, environment and agent setup before development, scoped per engagement.
    Infrastructure responsibility
    Model hosting is part of the engagement, run by your team or ours as agreed.
    Ongoing management
    Optional ongoing model and infrastructure management.
  • No model infrastructure to run

    Claude Code / OpenAI Codex Engineering

    Accelerated AI Development

    Expert-led delivery using Claude Code and/or OpenAI Codex with approved cloud-model configurations. You buy our engineering capability, not a resold AI subscription.

    Best fit

    Teams that can approve commercial AI coding tools and want an AI-first workflow without hosting models.

    AI processing environment
    Claude Code and/or OpenAI Codex, processed by the provider under account settings agreed with you.
    Setup
    Accounts, repository access, data handling and retention settings agreed before development.
    Infrastructure responsibility
    No dedicated model infrastructure for this delivery approach.
    Ongoing management
    Tool administration and access reviews; product operations are scoped separately.

Both packages include

  • Experienced engineering oversight
  • Product design, as scoped
  • Professional QA
  • Security-conscious reviews
  • Controlled releases
  • Documentation
  • Agreed handover

Not sure which fits? We'll recommend one during scoping.Compare AI delivery options

How we build

Leading AI agents.
Experienced people in charge.

Our AI engineering harness connects leading coding agents (Claude Code, OpenAI Codex or privately hosted models) to your project's context, tools and tests. Specialists scope every task, review every change and decide what ships.

    • How AI assists

      AI speeds up synthesis of permitted research, exploration and prototyping.

    • What our experts own

      Designers own usability, accessibility, consistency and validation with real users.

    • How AI assists

      Coding agents implement, refactor and draft tests and documentation.

    • What our experts own

      Engineers own the architecture, review changes and make the technical decisions.

    • How AI assists

      AI drafts test cases, analyzes coverage and helps investigate defects.

    • What our experts own

      QA specialists test against requirements and decide whether a release is ready.

    • How AI assists

      AI helps write infrastructure code, read logs and diagnose issues.

    • What our experts own

      DevOps engineers review configuration and approve every production change.

  • ReviewedBy engineers, before merge
  • ValidatedAgainst your requirements
  • ReleasedThrough controlled releases

How We Work

Five phases.
Quality from day one.

QA, security and DevOps start in the first week and continue through every phase. They're not a final checkpoint.

Illustrative delivery plan

ExampleGo-live

Throughout delivery

QA & security
DevOps

An example plan. Every project is scoped individually.

Phase 01Weeks ⁦1–3⁩

Discover & design

We clarify goals, users and constraints, then map the key journeys and prototype them. AI speeds up exploration; experienced designers decide what serves your users and your business.

  • Goals & scope
  • User journeys
  • Prototypes

Phase 02Weeks ⁦3–4⁩

Architect & define boundaries

Engineers set the architecture, data flows and integrations, and we agree which AI tools may be used, where processing happens and what they can access. QA plans tests from the requirements.

  • Architecture
  • AI tool boundaries
  • Test plan

Phase 03Weeks ⁦4–10⁩

AI-assisted implementation

Engineers break the work into scoped tasks and coordinate coding agents to implement, refactor and draft tests. Changes are reviewed before they're merged, and you see progress in regular demos.

  • Scoped tasks
  • Reviewed changes
  • Regular demos

Phase 04Weeks ⁦5–11⁩

Review & validate

QA specialists test against requirements and real user behavior, with AI helping draft tests and investigate defects, plus risk-based security and performance reviews. Issues are fixed before release, not after.

  • Automated tests
  • Exploratory QA
  • Release sign-off

Phase 05Weeks ⁦11–12⁩, then ongoing

Release & operate

DevOps manages controlled releases with monitoring, recovery plans and documentation, using AI to help diagnose issues. After launch, we keep improving the product under an agreed support scope.

  • Controlled releases
  • Monitoring
  • Handover & support

Connected systems

Make your tools work together.

Payment flows, customer data, communications and business workflows. Explore the scope and prerequisites for each integration.

FAQ

Frequently asked questions

What does Canvas Developers do?

We build software of every kind: startup MVPs, SaaS platforms, web and mobile apps, business and enterprise systems, e-commerce and integrations, plus AI features when a product needs them. Our engineers, designers, QA and DevOps specialists work with leading AI coding agents, so delivery moves faster while people stay in charge of every decision. SEO and digital growth remain available as a secondary service.

Can you build our startup MVP or mobile app?

Yes. We help you decide what the first version must include, then design it, build it for the web, iOS or Android, test it and launch it. AI coding agents keep the build fast; engineers make the architecture decisions so the product can grow beyond its first version, and we can keep improving it after launch.

Does my product need an AI feature to work with you?

No. We use AI to build software, and we build AI into software only when the product needs it; those are different services. A web app, SaaS platform or internal tool without AI features still benefits from AI-assisted engineering, QA and operations.

Who is responsible for work that AI helps produce?

Our team is. Engineers own the architecture and review changes before they're merged, QA specialists decide whether a release is ready, DevOps engineers approve production changes and designers own the experience. AI speeds up the work; it doesn't make those decisions.

What's the difference between the two development packages?

Private / Local AI Engineering uses privately hosted models inside infrastructure you control or an agreed isolated environment. Claude Code / OpenAI Codex Engineering uses Claude Code and/or OpenAI Codex with cloud settings your organization approves, with no model infrastructure to run. Both follow the same engineering, design, QA and release standards.

Can we hire you for QA, DevOps or UI/UX only?

Yes. Each capability can be engaged on its own: independent QA for software built by any team, DevOps and infrastructure work including ongoing operations, or UI/UX design without development. Scope and deliverables are agreed per engagement.

What happens after launch?

We can stay on under a scoped support engagement covering releases, maintenance, regression testing, infrastructure and monitoring, and AI agent or model operations where relevant. Support hours, response commitments and exclusions are agreed up front.

Can you finish an app made with Lovable, Bolt, Replit or Cursor?

Yes. We start with a scoped paid assessment of the code, data, authentication, integrations and deployment. You receive findings and a completion plan before committing to the full work. A rewrite is only proposed when the evidence supports it.

Where are you based, and how do we start?

Our office is in Dhaka, Bangladesh, and we work with clients worldwide. Use the contact form, email support@canvasdevs.com or WhatsApp +8801755564028. Tell us what you want to build, improve or connect so we can discuss the next step.

Your next step

Let’s talk about your project.

Tell us what you want to build, what is already working and where you need help. We’ll clarify the next step with you.