Prepare your SaaS for an AI agent future.
Get a plan that uncovers AI-driven workflows to grow revenue per user, keeps your product central as agents reshape your market, and protects your user base from AI-native competitors.
Grow revenue per user.Become agent-ready.
The agent future creates two imperatives: capture more value from every user through AI-powered workflows, and position your product as the tool agents choose. We prepare you for both.
AI workflows that expand revenue per user
Map real workflow friction and design AI-powered experiences that keep users inside your product longer, automate the steps they currently leave to do, and unlock upgrade paths they didn't know they needed.
- AI interventions scored for revenue impact
- Deeper workflow integration that reduces churn
- Competitive differentiation through workflow intelligence
Ready your product for AI agent consumption
The next generation of users won't interact with your product directly — their agents will. We design the surface that makes your product the tool agents discover, interact with, and depend on.
- Product structured for agent discovery and interaction
- APIs and data surfaces designed for agentic orchestration
- Positioned as the default tool in agent-driven workflows
Your SaaS was built for human users.The future runs on agents.
You're leaving revenue on the table.
Your users hit friction every day — manual steps, context switching, repetitive decisions. In an agent-driven world, each of those moments is an opportunity for AI to keep users inside your product doing more, upgrading faster, and getting deeper value. Instead, agents are routing them elsewhere.
AI-native competitors are taking your users.
A new wave of startups is building agentic-first products that own a larger share of your users' workflows. They don't just add AI features — they reimagine the entire workflow around what agents can do. Your product solves one step. Theirs orchestrate the whole chain. And every month, the switching cost drops.
Guessing wrong costs more than the assessment.
Building the wrong AI feature wastes 3–6 months of engineering and burns credibility with your users. The AI features that actually drive revenue and retention are rarely the ones on your current roadmap. You need clarity before you commit resources to an agent-ready future.
What you walk away with.
Four artifacts built from deep user and workflow research. Each one maps AI opportunities to revenue growth and retention — specific to your product, your users, and the agent-driven future of your market.
Workflow & Revenue Opportunity Audit
A complete map of your users' workflows, goals, and friction points — scored for revenue impact. Where your product fits in the bigger picture, where users drop off or work around you, and where AI-driven workflows can expand what they do and pay for.
User-Centered Insight Synthesis
Key user problems, goals, and workflow friction distilled into a decision framework. Which AI interventions will drive upgrades and expansion revenue, which will reduce churn in an increasingly agentic landscape, and which ones sound exciting but won't move the needle.
Data Readiness & Competitive Moat Assessment
What data you have, what gives you a defensible edge, and what needs to be structured before AI features ship. Plus: how to make your product accessible to external AI agents — so they route through you, not around you — without exposing the advantages that make you irreplaceable.
AI Growth & Agentic Blueprint
A concrete plan for how AI solves the specific problems uncovered in the audit. Which features grow revenue per user, how agents will interact with your product, and how the experience evolves for both human users and AI agents — keeping you central as your market automates.
8–12 weeks. Fixed scope.
A disciplined, time-boxed engagement designed to produce clarity and a concrete growth plan — not billable hours.
Intake & Discovery
Product walkthrough, data architecture review, revenue and usage analytics mining, and stakeholder alignment. We learn how your product works, who pays for what, and where the real friction and revenue gaps live.
User Research & Workflow Mapping
Deep-dive user interviews, workflow decomposition, and pain point identification. We map what users are trying to accomplish, where they leave your product to get it done, and where AI can genuinely help — both for human users and for the agents acting on their behalf.
Analysis & Blueprint Development
Synthesis of findings into the four deliverables. Revenue opportunity scoring, retention risk mapping, data readiness assessment, and the AI growth and agentic blueprint take shape.
Review Workshop & Final Artifacts
Interactive review sessions with your team. Challenge assumptions, pressure-test revenue projections, refine priorities, and walk away with final deliverables you can act on immediately.
Who this is for. And who it isn't.
Good fit
- B2B SaaS founders and product leaders at $500K–$5M ARR
- Teams seeing users leave to AI-native competitors or agent-driven workarounds
- Products where users have complex workflows that AI could simplify
- Leaders who want to grow ARPU and become agent-ready, not just add AI for the sake of it
- Companies thinking about how agents will reshape their market — and how to profit from it
Not a fit
- Pre-revenue startups still exploring product-market fit
- Teams looking for someone to build and ship AI features
- Companies that need vendor selection or model benchmarking
- Organizations without product usage data or user access
- Anyone looking for a generic AI roadmap deck
Fixed scope. Concrete outcomes.
$30,000
One wrong AI feature costs more than this in wasted engineering alone. This engagement gives you the clarity to build the right thing first — the features that grow revenue per user and keep your product central as agents reshape your market.
What's included
- All 4 deliverable artifacts
- 8–12 week structured engagement
- Review workshop with your team
- 30 days of follow-up access for questions
- Revenue opportunity scoring per AI intervention
- Prioritized build roadmap your team can execute on
- Decision insurance for executive-level clarity
- Risk reduction before committing engineering resources
- Avoidance of wasted effort on the wrong AI features
- Strategic alignment during a generational platform shift
What you avoid
- Months of internal debate with no resolution
- Building AI features that don't move revenue
- Costly wrong-first-move implementations
- Losing users to competitors who became agent-ready first
Common questions.
The agent future is coming.Own your position in it.
8–12 weeks. Four artifacts. A plan built on real user research — tied to the AI features that grow ARPU, protect your user base, and make your product the one agents choose.