AI Transformation for B2B Software Companies
AI-Native Engineering for B2B Software.
Ship Faster. Protect ARR. Win New Logos.
What we hear from portfolio companies
You don't need another advisor. You need an execution partner who's done this before.
Our Approach
People. Process. Product.
Good companies do one. Great companies do two. The ones redefining their market do all three.
01
AI Foundations
Make every team member more productive with AI. Engineers ship faster with AI-assisted coding. Non-technical teams automate repetitive work.
Table StakesProductivity
02
AI in Operations
Redesign internal workflows and processes around AI to drive cost savings and efficiency. This is where AI starts showing up on the P&L.
Rapid ResultsCost Savings
03
AI in Core Product
Integrate AI into your core product to defend your competitive position and unlock new revenue.
RevenueCompetitive Edge
Production-Grade AI
Deploying AI into production in regulated industries.
Getting AI past the pilot in a regulated environment takes more than a model — it takes control, integration, and trust.
Control & Visibility
Full observability and monitoring across every AI decision, with guardrails that keep the system inside safe bounds. We build evaluation-driven — golden datasets and hard measurements — so quality is proven, not assumed.
Integrated, Not Rebuilt
AI deployed into the systems, data, and workflows you already run — no rip-and-replace. We meet your architecture where it is, so you capture value without a ground-up rebuild.
Secure & Compliant by Design
Deployed inside your environment with access controls, data governance, and audit trails built in — so you satisfy security teams and regulators without slowing delivery.
Our Services
How we can help
AI Product Opportunity Assessment
A discovery sprint that validates where AI will actually move the needle — across product, business, technical, and data dimensions — so you invest in the right things first.
2–4 weeks
Operational AI Automation
End-to-end automation of repetitive, manual workflows — from use case discovery and prioritization through to production deployment, change management, and team handover.
8–10 weeks
Full Lifecycle AI Product Delivery
We take full ownership of the AI product lifecycle — from opportunity mapping to building, testing, and deploying AI agents in your infrastructure, then transitioning to your internal team.
“Fix AI Product” Sprint
A focused engagement to diagnose and rebuild AI products that shipped fast but aren’t reliable in production — restoring development velocity and customer trust.
8–10 weeks
Evaluation & LLMOps Setup
We set up the operational infrastructure — evaluation frameworks, monitoring, and data labeling pipelines — so your team can iterate on AI products with confidence instead of flying blind.
6–8 weeks
