AI Tooling

AI tools wired into how your team works.

We build internal assistants, agents and developer tooling connected to your systems, with clear limits on what they can see, what they can do and what they cost.

Is this for you?

Sound familiar?

If any of these describe where you are, this is the right place to start.

Knowledge is scattered across wikis, tickets and drives, and answers take hours to find.

Teams repeat the same multi-step tasks across five systems every day.

You want coding agents across engineering, with controls your security team will approve.

An AI prototype works in a demo, but you can’t tell if it’s getting better or worse.

Scope

What we build.

Tools that sit inside your existing systems and permissions, so they get used and stay safe.

01

Knowledge assistants & search

Retrieval over your documents, tickets and code, with citations and permissions that match your existing access rules.

02

Agents & workflow automation

Agents that take multi-step actions across your systems, with approval steps wherever a mistake would be expensive.

03

MCP servers & integrations

Secure Model Context Protocol servers that give assistants and coding agents governed access to internal tools and data.

04

Coding agent rollout

Coding agents configured with your codebase context, conventions and guardrails, plus the practices that make them productive.

05

Evaluation & observability

Task-specific test sets, regression runs and tracing, so every model, prompt or provider change comes with evidence.

06

Cost control & model routing

Spend limits, caching and routing between models, so you pay for top-tier quality only where it matters.

Our product

Koda Code

Our desktop coding agent. We build it and use it on every engagement, and we can configure it for your team, your models and your policies.

  • Runs on macOS, Windows and Linux
  • Works with the model provider you choose
  • Understands your project through a local code graph
  • Asks before running commands you haven’t approved
  • Extends with MCP servers, skills and hooks
Process

How it works.

Short loops and written decisions, so you always know what’s happening, what it costs and what comes next.

  1. 01 · Week 1

    Map

    Workflows, systems, data access and risk, plus the measure that defines success.

  2. 02 · 2–3 weeks

    Prototype

    A working tool on real data, with an evaluation set from the very first version.

  3. 03 · 2–4 weeks

    Harden

    Permissions, audit logging, monitoring, cost controls and a security review.

  4. 04 · Staged

    Roll out

    Gradual release, admin training, and usage and quality dashboards.

Engagements

Ways to engage.

Every engagement starts with a free 30-minute call and a written proposal. No surprises on scope or price.

Platform build

A shared AI platform: model gateway, MCP servers, evaluations and several tools.

Pricing
Fixed, after discovery
Length
8–16 weeks

Managed improvement

Ongoing evaluation runs, model updates and new capabilities.

Pricing
Monthly
Length
Month to month
FAQ

Questions we hear often.

Yes. We deploy into your AWS, Azure or Google Cloud accounts, or on-premises, and can use models hosted in your own environment where data rules require it.

Have a workflow worth automating?

Walk us through it on a call. We’ll tell you whether an AI tool will help and what a first version would look like.