Industries / Technology & SaaS
Finance foundations and AI strategy for technology companies that scale fast.
SaaS and technology companies must build AI into the product while keeping the company's own finance and operations ahead of growth. We work on both sides of that equation.
- Who we work with
- SaaS, software and platform companies from growth stage to public
- Where we start
- Revenue and finance operations, AI product strategy, expansion
- What changes
- Predictable metrics and a clear AI roadmap
Where the pressure is.
Technology companies grow faster than their back office. Billing, revenue recognition and investor reporting become hard to trust at exactly the moment they matter most.
At the same time, every product team is asking which AI features will differentiate and which will become commodity as models improve.
- 01
Revenue and metric reporting
ARR, churn and billing complexity make numbers hard to reconcile.
- 02
AI product strategy
Which features differentiate, and which become commodity.
- 03
Finance not keeping pace
Close, controls and forecasting built for a smaller company.
- 04
International expansion
New entities, currencies and tax obligations arrive faster than the team.
Where AI changes the work.
Six places we typically start in Technology & SaaS. Each is a workflow, not a tool.
Subscription revenue and billing automation
Cleaner revenue workflows from contract to ledger.
Finance Transformation →Board and investor metric reporting
One definition of each metric, produced on a reliable cycle.
Finance Transformation →AI product opportunity assessment
Where AI creates durable value for your customers.
AI Transformation →Customer support and success agents
Agents that resolve routine requests and hand off the rest.
AI & Agentic Workflows →Pricing and packaging analysis
Evidence for pricing decisions, tested with data.
M&A Growth Strategy →Market entry for new regions
Entity, hiring and go-to-market planning for expansion.
Global Market Entry →
One workflow, redesigned.
People, process, data, AI and controls are redesigned together around the outcome. Judgment stays with people.
- Data & systemsProduct, billing and finance systems are connected.
- AI agentsAgents reconcile, draft and surface anomalies.
- WorkflowClose and reporting run on one governed process.
- Human decisionFinance leaders review and decide.
- OutcomeMetrics the board and investors can trust.
Human decision point: senior judgment is built into the workflow, not added afterwards.
Control stays where it matters.
- Customer data handling and model training boundaries
- Quality and safety review for AI product features
- Revenue recognition controls
- Vendor and model dependency risk
What clients can expect.
Reliable metrics
Numbers that reconcile across finance, product and the board.
A focused AI roadmap
Fewer, better bets on where AI belongs in the product.
Faster entry into new markets
A tested plan for the next region.
Illustrative outcomes. Specific measures and targets are agreed at the start of each engagement.