Build with AI.
Ship inside your stack.

Describe what your team needs. Avokaido builds it in your approved frameworks, inside the guardrails your platform and security teams set once, and opens a pull request in your own repository.

Create workspace See how it works

Your own repositories
Your own AI keys
10% on token spend, hosting and infrastructure

avokaido.app / build

Request

Build an internal approval dashboard for expense reports, with role-based sign-off and an audit trail.

Building

Scaffolding Spring Boot service
Applying tenant isolation and RBAC
Generating tests, coverage 84%
Opening pull request on your GitHub

acme/expense-approvals PR #128 opened

Representative interface

Built for teams moving from prototype to production.

Startups

Move from first version to something a customer can depend on.

Security-led SaaS

Ship quickly under isolation, access and audit requirements you already have.

Prototype graduates

Bring an AI-generated prototype into a repository your engineers can review and own.

From request to repository.

The same path every time, whether the request comes from an engineer or from the person who actually has the problem.

01
Request

Someone describes what the team needs, in plain language.
02
Build

Avokaido writes it using the frameworks and patterns you approve.
03
Govern

Your access rules, isolation and quality gates are applied as it builds.
04
Verify

Tests are generated and run before anything leaves the platform.
05
Deliver

A pull request lands in your repository for your team to review.

Expense Approvals 3 pending

Travel, Q2 offsite €1,240

Software licences €860

Client dinner Approved

Signed off by: Finance lead Logged to audit trail

Representative interface

Applied automatically

Access: Role-based sign-off, scoped to your directory groups
Isolation: Workspace and data kept separate from every other tenant
Audit: Every approval and every build action recorded
Tests: Generated with the service, run before the pull request opens

More people can build.
Engineering still decides how.

The person closest to a problem is rarely the person with room on the roadmap. Avokaido closes that gap without moving control out of engineering.

Business teams and domain experts

Describe what they need

Operations, finance, support and product people request real applications in plain language. No ticket, no queue, no translating the requirement for someone else to interpret.

Engineering and IT

Define how it gets built

Approved frameworks, security level, tenant isolation, quality gates, audit trail and the repository every result lands in. Configured once, applied to every build that follows.

IT stops being the bottleneck without becoming the owner of work it never saw.

Software can look finished long before it is production ready.

The interface is the part everyone reviews. Underneath it sit the logic and the data, and that is usually where quality quietly gives way.

Interface Skin: What users see, and the boundary you deploy behind.
Logic Flesh: The services, permissions and rules that actually run the product.
Data Stone: The core your users trust you with, and the hardest part to fix late.

Avokaido builds through all three layers, and keeps checking them after release.

See what is inside

What teams build with it.

Real applications in your own stack, on your own domain, in your own repositories.

Internal tools and workflows

The work that never reaches the top of the backlog because it only affects one team.

Approval flows
Admin panels
Operations dashboards
Reporting

Customer-facing applications

Production software on your own domain, with isolation and access control from the first commit.

Customer portals
Booking flows
Onboarding journeys
Self-service

Automations and integrations

Connective work across systems you already run, instead of another manual process.

System integrations
Scheduled reporting
Data sync
Internal APIs

Use the stack you already trust.

Avokaido builds inside the tools your team runs today. Nothing here asks you to migrate first.

AI models

Claude
OpenAI
Gemini
Ollama

Repositories

GitHub
GitLab
Bitbucket
Git

Runtime

AWS
Azure
GCP
On-premise

Issue tracking

Jira
Linear

Languages and frameworks

Know what you shipped, every week.

Building quickly only helps if quality stays visible afterwards. Avokaido scans each repository weekly and reports what changed underneath.

acme/expense-approvals Week 34

Test coverage 84%

Up 6 points since the service was generated.

Untested paths

PaymentRetryService.retry()
ApprovalRules.escalate()

Complexity hotspot

ReportBuilder.compose() quadratic, trending up

Suggested: generate tests for both retry paths

Example report

Coverage: Every test classified by type, with untested code and missing cases listed.
Complexity: Big-O analysis flags the functions getting slower before they cause incidents.
Next steps: Concrete suggestions and generated tests, not just a score.

Start monitoring

Built inside your security model.

Security is not a tier you upgrade into. Your platform and security teams set the guardrails once, and every application the business builds after that inherits them.

01 Identity
02 Workspace isolation
03 Approved models
04 Repository
05 Runtime
06 Audit

Identity

SSO and SAML: Bring your own identity provider, with SCIM provisioning.
Role-based access: Granular roles decide who builds, who reviews and who ships.

Data

Encrypted end to end: In transit and at rest. Your keys and secrets stay yours.
No training on your data: Code and prompts are never used to train any model.
Tenant isolation: Every workspace runs separately, with no shared data plane.

Infrastructure

Self-hosted option: Run Avokaido in your own cloud or on-premise when policy requires it.
Your repositories: Everything lands in your own GitHub, GitLab or Bitbucket.

Governance

Audit logging: Who built what, when, and with which model.
Quality gates: Tests and standards enforced before code leaves the platform.

GDPR-ready Today

SOC 2 Type II In progress

ISO 27001 Planned

Speed without the enterprise tax.

Seat-based tools make collaboration expensive. Building it in-house is slow. The trade-off is not actually necessary.

Avokaido compared with seat-based AI tools and building in-house
Dimension	Avokaido	Seat-based AI tools	Build in-house
Pricing model	10% on token spend	Per-seat licences plus usage tiers	Salaries plus infrastructure
Cost as the team grows	Invite everyone, no per-seat cost	Every seat adds to the bill	Every hire adds to the bill
Time to first app	Minutes	Days to onboard	Months
AI models	Bring your own Claude, GPT and Gemini	Usually one vendor model	Your integration to maintain
Code ownership	Your repositories, no lock-in	Often locked to the vendor	Yours
Security and governance	You set the level: isolation, audit, GDPR	Vendor-defined	Built in-house, slowly
Ongoing quality	Weekly repository monitoring included	An add-on, or nothing	Build it yourself

10% on token spend

That is the entire bill.

You pay your AI provider for what you use, and Avokaido adds a single percentage on top. Repository monitoring is billed separately, per repository.

Bring your own keys: Claude, OpenAI and Gemini bill you directly. You own the provider relationship and you see the raw usage.
One percentage on top: Added transparently to token spend. No platform fee, no minimum, no annual commitment.
No seats, no tiers: Invite the whole organisation. Pricing never becomes the reason to limit who can build.

See how the maths works

Teams that needed both.

Our domain experts ship the tools they used to wait two quarters for, and everything still lands in our GitHub, inside the guardrails we set.

Head of Platform Regulated fintech

Bring-your-own-keys plus a flat 10% made the budget conversation trivial. No seats to negotiate, no tier to outgrow.

VP Engineering Series B SaaS

The weekly repository monitoring caught coverage gaps and complexity creep before they ever reached production.

Engineering Manager Healthcare platform

Questions, answered.

How does pricing actually work?

You bring your own AI provider keys and pay those providers directly for tokens. Avokaido adds a flat 10% on that token spend. There are no seat licences, no usage tiers and no platform fee. Repository monitoring is billed separately at a per-repository monthly rate.

Do I bring my own AI keys?

Yes. Plug in your own Claude, OpenAI and Gemini keys. The provider bills you directly for usage, so you keep full control of spend and the commercial relationship. We never resell tokens.

Where does my code live?

In your own repositories on GitHub, GitLab or Bitbucket. Everything Avokaido builds is pushed to your version control, so there is no lock-in. If you leave, you keep every line.

Is my code or data used to train models?

No. Your code, prompts and data are never used to train any model, ours or a provider’s. Data is encrypted in transit and at rest, and each workspace is tenant-isolated.

How do you handle security and compliance?

You set the security level. Tenant isolation, role-based access, audit logging, SSO/SAML and GDPR-ready data handling are built in, with a self-hosted option for stricter policies. SOC 2 Type II is in progress and ISO 27001 is planned.

Do I have to talk to sales to get started?

No. You can self-serve and create a workspace in minutes with GitHub, Google, Microsoft or Apple. If you would rather see it on your own stack first, you can book a demo and we will walk you through it.

What can my team actually build?

Internal tools and workflows, customer-facing apps on your own domain, and automations that connect the systems you already run. Across Java, .NET, Python, Go, Rust, React, Angular, Vue, Flutter and more.

Start building today.

No sales call required. Most teams have a workspace running in a few minutes.

01 Create a workspace with GitHub, Google, Microsoft or Apple.
02 Connect your own Claude, GPT or Gemini keys.
03 Set your security level, then start building.

Create workspace

Dedicated onboarding and hands-on support are part of the platform, not an upgrade.

Or see it on your stack first

A 30-minute walkthrough on your own use case, with a security and governance review for your team.

Build with AI.Ship inside your stack.