Industries
Software & Technology
For CEOs of software companies, SaaS businesses and IT services firms. Your board wants AI in the product, your engineers are trying coding agents with mixed results, and customer security reviews now ask about AI. We help you ship AI features and adopt AI in engineering without lowering the bar.
What we hear from software and technology leaders
"Where's the AI in the product?"
Customers, competitors and your board all ask. A chat window bolted onto the side won't hold up against a competitor who built AI into the workflow.
Coding agents, mixed results
Some engineers swear by them. Others spend the time saved reviewing pull requests that miss the point. Nobody has set the standard for the team.
Security reviews ask new questions
Enterprise prospects now send AI security questions: which providers touch their data, whether it's used for training, and how you keep one tenant's data from reaching another.
Where AI pays off first
AI features inside your product
An assistant that answers questions about the customer's own data, drafts the next step, or takes actions with the user's permission, built on your existing APIs and permission model. What to track: weekly use of the feature.
In-App AI Assistants: AI features inside your productCoding agents on a mature codebase
Specs grounded in your code, independent review, evidence for every change and a human merge gate, so agents produce work your senior engineers will approve. What to track: agent pull requests merged without rework.
Software Development Acceleration: Coding agents on a mature codebaseTest coverage that keeps pace
Agents that write and maintain tests from specs and bug reports, reviewed like any other code. What to track: defects that reach customers.
QA Testing Automation: Test coverage that keeps paceSupport that knows your product
How-to questions answered from your docs, release notes and past tickets, with bugs handed to engineering with steps to reproduce. What to track: tickets resolved without engineering.
Customer Support Automation: Support that knows your productGuardrails customers will ask about
Tenant isolation, retention, provider terms and audit logs for every AI feature, written up so your team can answer security questionnaires. What to track: days to return a questionnaire.
AI Security & Privacy Guardrails: Guardrails customers will ask about
What's different about software and technology
Multi-tenant data
An AI feature must never show one customer another customer's data. We enforce your existing permissions when the AI retrieves data, and test for cross-tenant leaks before launch.
SOC 2 and customer contracts
A new AI provider can mean a new subprocessor, customer notices under your data processing agreements, and new controls for your auditors. We document each build so your security team can update all three.
A codebase with history
Coding agents look great on clean demos and struggle on years of real code. The harness around the model decides whether they help, and that's the work we do with engineering teams.
How we'd start
Interview leadership about product strategy and where customers want AI.
Map the work in engineering, product, support and customer success.
Review your architecture, data model, permissions and current AI use.
Rank every opportunity and start with one product feature or one engineering team.
Common questions
Should our own team build the AI features?
Usually, yes, with us helping design, review and harden them. Where you lack capacity, our senior developers build alongside your team and hand the code over.
How do we get engineers to trust coding agents?
AI adoption in engineering starts with one team on real work, not a demo. Agree what an agent may change and who approves it, then improve the setup each week from what review catches. That's our engineering enablement work.
What is PRFlow?
An open-source project I lead: a harness that makes AI coding agents dependable on real, mature codebases. It's in daily use by hundreds of developers, and it shapes how we run engineering enablement.
Which AI models and providers do you use?
Whichever fit the job and your contracts. We design so you can change providers later without rebuilding the feature.
Related solutions
Let's find where AI pays off in your business.
Thirty minutes with Daniel. No pitch deck: you talk about your business, I tell you honestly where AI fits and where it doesn't.