Fractional CTO for B2B SaaS
Not a generalist — a fractional CTO who has shipped multi-tenancy, billing, enterprise security, and AI features, and who knows the SaaS model changed after AI.
Why Building SaaS Changed After AI
Most "fractional CTO for SaaS" advice still describes the 2021 playbook. The model has shifted under everyone — the architecture, the pricing, and the moat are all different problems than they were two years ago. I've been doing exactly this strategy work, most recently redesigning a platform's business model around agent consumption and usage pricing at MateBio.
The Seat Is Dying
Per-seat pricing assumes a human logs in and clicks. Increasingly the thing consuming your product is an agent — yours or your customer's — and one API or MCP connection can front unlimited end users. A seat has no meter for that. Seat-based pricing is already down to roughly 15% of B2B SaaS, and Salesforce is openly rebuilding around agents that work with nobody in the seat. I build metering for consumption, not headcount, before that bites.
Hybrid Pricing, and Margin Is Now an AI Problem
The default model is now hybrid — a platform fee plus usage plus overage — and it's the fastest-growing structure in B2B SaaS. Meanwhile every AI feature carries a real per-call cost, so gross margin has become a pricing-and-architecture decision, not an afterthought. I wire the metering and per-account cost controls so you can change pricing without an engineering project, and so an AI feature doesn't quietly turn an 80% margin into 40%.
The Moat Moved
AI commoditizes what used to be defensible — integrations, data curation, even your schema or ontology. What's left as a real moat is proprietary data with network effects, workflow lock-in, and eventually outcomes. I help you spend engineering on the new moat instead of on the parts AI just made cheap.
One caution, because it's everywhere right now — not everything moves to outcome-based pricing. It works when the outcome is fast and clearly attributable to your product, the way Salesforce can charge per closed deal. It's a trap when outcomes are slow or binary. I saw this directly at MateBio, where the "outcome" is a 10-year, billion-dollar drug approval you can't run a SaaS P&L against. Knowing which kind of business you are is the call I help founders make before they copy someone else's pricing.
The Four Things SaaS Founders Actually Hand a Fractional CTO
Strip away the titles and most B2B SaaS engagements come down to these four. Each one is cheap to get right early and brutally expensive to retrofit.
1. Multi-Tenant Architecture
Tenant isolation, a data model that won't need a rewrite at customer 50, and a noisy-neighbor strategy so one account can't degrade the rest. The choice between shared, siloed, or pooled tenancy is made once — I make it deliberately.
2. Metering, Billing & Hybrid Pricing
Trustworthy metering and entitlements wired to your plans, on a billing stack (Stripe, Orb, or similar) built for hybrid pricing — platform fee plus usage plus overage — and for agent or API consumption, not just per-seat. This is what keeps your pricing model from being frozen by your codebase when the market moves off seats.
3. Security & Compliance for Enterprise Sales
RBAC, audit logs, SSO, encryption, and a SOC 2 path scoped to what actually unblocks deals — not a checklist that stalls the roadmap. The goal is to answer the security questionnaire in days, not quarters.
4. AI Features That Don't Leak Data or Money
Most SaaS roadmaps now have an AI line item. I ship RAG and agentic features with tenant-aware data boundaries, cost controls per account, and a multi-provider fallback — so an AI feature improves retention instead of quietly destroying gross margin. And when customers reach you through their own agents, I expose curated, metered surfaces rather than a generic endpoint that lets them take down your database or rebuild your margin layer on top of you.
B2B and B2C SaaS Are Not the Same Build
It's worth being blunt about this, because the wrong reference architecture wastes months. B2C SaaS is a scale-and-latency game: millions of light sessions, viral signup flows, and cost-per-user measured in cents. B2B SaaS is a trust-and-control game: fewer accounts, each worth far more, each demanding isolation, permissions, an audit trail, and an admin who wants to see everything their team does.
I focus on B2B. That means I optimize for the things that close and renew enterprise contracts — provisioning, roles, security posture, and uptime that survives a procurement review — rather than for consumer-grade virality. If you're selling to other companies, those priorities are the difference between a product that demos well and one that passes legal.
This is also why a generic "CTO as a service" arrangement isn't enough on its own for SaaS — the deliverable isn't generic tech leadership, it's the specific B2B SaaS architecture that makes you sellable to a 500-person company.
Case Study: Scaling an Established B2B SaaS Platform
As Director of Engineering at Cascade, the strategy-execution platform, I led the Integrations, Metrics, and Reports teams and sat on the global Product Leadership Team — fully remote across time zones. Cascade is a mature multi-tenant B2B SaaS serving enterprise customers, so the work was about scaling a product that already had demanding buyers, not finding product-market fit.
Key outcomes:
- Built the Metrics Library — a front end, serverless functions, and an ingestion pipeline that let customers pull their core metrics directly from business systems, data lakes, BI tools, and spreadsheets, and align them to goals and targets. The enterprise-integration surface that every B2B SaaS eventually has to build.
- Designed the integration architecture on AWS serverless so the pipeline scaled with customer data volume without standing up dedicated infrastructure per tenant.
- Made engineering investment legible to the business with a Balance Framework — turning resource allocation across teams into a data-informed decision rather than a negotiation.
- Hired tech leads and principal engineers and served as the technical point of reference across Engineering, Product, and Customer Success — the durable team that keeps a B2B SaaS shipping as it grows.
Case Study: Scaling an AI SaaS Platform for Biotech
As CTO at MateBio, I led the transformation of raw biomedical knowledge-graph data into a scalable, defensible, commercially viable SaaS platform. MateBio gives wet-lab researchers at biotech and pharma companies AI-powered tools to explore complex biological relationships through natural-language queries.
Key outcomes and contributions:
- Architected a GraphRAG system that translates biomedical questions into Cypher queries against Neo4j, with entity recognition, provenance tracking, and confidence scoring.
- Introduced load-balanced and secure APIs to support enterprise-grade deployments for biotech and pharma customers.
- Built analytics foundations to understand adoption across use cases, users, and institutions — directly feeding product prioritization.
- Developed interactive 2D and 3D graph visualizations helping researchers navigate biological pathways and relationships.
- Implemented real-time streaming and progress indicators to keep complex AI queries transparent under load.
- Led the business-model redesign — moving the platform off ad-hoc seat pricing toward a hybrid platform-fee-plus-usage model built for agent (MCP) consumption, and mapping where outcome-based pricing genuinely applies versus where it's a trap. Post-AI, the pricing model is as much a CTO problem as the architecture.
Fractional vs. Full-Time CTO for a SaaS Startup
A full-time CTO for a SaaS startup costs $250K+ in salary plus meaningful equity. Before product-market fit, that's the wrong spend — you're paying executive comp for work that is mostly architecture and hands-on building, not org-scaling. A fractional CTO gives you the senior judgment on the four decisions above without the cap-table dilution.
The honest version: hire fractional while the questions are technical — what to build, how to make it multi-tenant, how to charge, how to pass security. Hire full-time when the questions become organizational — managing 15+ engineers, owning a multi-year roadmap, sitting on the exec team. Part of my job is telling you when that line has been crossed and helping you make the transition cleanly.
If you're a US-based SaaS startup, the same logic applies with a time-zone advantage — see fractional CTO for US startups.
How Engagements Are Structured
Most SaaS engagements start with an assessment, then move to advisory or an embedded build slice depending on how much you need shipped. Full detail lives on the pricing page.
SaaS Tech Assessment
$4,000
A deep dive into your multi-tenancy, billing, security posture, and AI plans, with a 90-day roadmap of what to fix first.
Advisory + Build Slice
$5K–8K/month
CTO guidance plus one bounded SaaS build per month — tenant isolation, billing, or an AI feature — to prove the riskiest assumption.
Embedded SaaS CTO
$10K–15K/month
Full technical ownership for SaaS startups that need leadership, delivery, hiring, and accountability for the platform.
Every engagement starts with a free consultation and runs month-to-month with 30-day notice. Cash only — no equity.
Frequently Asked Questions
When should a B2B SaaS startup decide on multi-tenancy?
Before the second paying customer, ideally before the first. The tenancy model — pooled, siloed, or a hybrid — shapes your data model, your security story, and your per-customer cost. Changing it later is one of the most expensive migrations a SaaS company can face, so it's the first thing I lock down.
Can a fractional CTO get us through a SOC 2 or security review?
Yes, and it's a common reason SaaS founders call. I scope the security work to what unblocks the deal in front of you — access controls, audit logs, SSO, encryption, and the SOC 2 path — rather than treating compliance as a project that swallows the roadmap. The aim is to answer the questionnaire in days.
How do you add AI features without blowing up our margins?
By treating AI cost as a first-class metric — per-tenant cost controls, caching, model routing across providers, and falling back to cheaper models where quality allows. I've built multi-provider abstractions over OpenAI, Anthropic, and Bedrock so an AI feature stays affordable as usage grows instead of quietly eroding gross margin.
Should we still price per seat?
Probably not as your only lever. Seats still work for the surface a human clicks. But the moment agents or APIs consume your product, a seat stops being a meter — one connection can front unlimited usage. Most B2B SaaS is moving to hybrid (platform fee plus usage), and I'd build the metering for that now even if you launch on seats, so you're not forced into a migration when your customers' agents arrive.
Is outcome-based pricing the future?
In specific cases. It works when the outcome is fast, measurable, and clearly attributable to your product — Salesforce can price per closed deal. It breaks when outcomes are slow or binary; at MateBio the outcome is a 10-year, billion-dollar drug approval you can't run a SaaS P&L on. I help you tell which kind of business you are before you copy someone else's pricing.
Do you build, or just advise?
Both, depending on the engagement. I ship production code alongside the team when that's what moves the needle — most SaaS startups before product-market fit need a builder more than a meeting. As you grow, the balance shifts toward strategy, hiring, and architecture review.
We're early and pre-revenue. Is a fractional CTO worth it?
Often more so, because the decisions that are cheapest to get right are made earliest. A short assessment plus advisory can save you from the multi-tenancy and billing rewrites that derail SaaS startups six months in — for a fraction of a full-time hire.
How quickly can you start?
For urgent situations — a technical co-founder left, an enterprise security review landed, a launch is slipping — I can start within 48 hours. For planned engagements, typically 1–2 weeks from our first call.
Let's Make Your SaaS Sellable to Bigger Customers
Whether you're choosing a tenancy model, wiring up billing, prepping for a security review, or shipping your first AI feature, let's talk through where your SaaS is and what to fix first.