Custom AI Revenue Architecture for B2B SaaS
I don't just advise on what software to buy. I build the custom architecture that replaces it.
Stop paying £100k/year for legacy platforms and AI wrappers. I architect and build custom, AI-driven revenue systems that replace bloated tech stacks, enforce strict governance, and return capital directly to your bottom line. These are production-ready systems built to scale — not theoretical advice.
The Frankenstein Stack Problem
Most B2B SaaS companies spend £300k–£500k annually on a fragmented GTM tech stack. CPQ from one vendor. CLM from another. Forecasting from a third. Billing from a fourth. Each tool solves one narrow problem while creating three new ones: data fragmentation, workflow rigidity, and governance gaps.
Then the "AI layer" arrives. Vendors bolt language model wrappers onto the same legacy platforms and charge a premium for features that don't fix the underlying architecture. You're not getting intelligence — you're getting a chatbot on top of technical debt.
The result is a stack where:
- Reps lose 3+ hours a week navigating clunky quoting workflows
- Contract data lives in four different systems with no single source of truth
- Forecasting tools ingest corrupted CRM data and produce confident-looking fiction
- Finance spends two weeks each quarter reconciling billing against what was actually sold
- Every new tool requires its own admin, its own integration, and its own annual renewal negotiation
The fix isn't another tool. It's architecture designed around how your business actually operates — built once, governed properly, and owned by you.
Custom AI-Powered Revenue Systems
Each system is designed from the ground up around your actual business logic, deal mechanics, and data model. No vendor data model. No 6-month implementation. No admin overhead.
Custom CPQ & Deal Desk
Logic-driven pricing engines built around your actual deal structures — multi-year ramps, usage-based components, partner margins, approval chains. Deployed in weeks, not the 6-month enterprise CPQ implementation cycle.
Replaces: Salesforce CPQ, DealHub, Subskribe, Conga
Typical legacy cost: £100k+/yr
Contract Lifecycle Management (CLM)
AI-enforced contract guardrails that handle generation, negotiation tracking, deviation alerts, and compliance — without the £50k platform license. Built to integrate directly with your CRM and deal desk.
Replaces: Juro, Ironclad, DocuSign CLM, PandaDoc
Typical legacy cost: £50k+/yr
Revenue Forecasting
Predictive models built directly on your clean CRM data — designed around your actual stage definitions and deal mechanics, not a vendor's generic overlay. Forecasting that reflects governance, not just pipeline math.
Replaces: Clari, BoostUp, Aviso
Typical legacy cost: £60k+/yr
Billing & Revenue Recognition
Custom financial workflows that handle invoicing, revenue recognition, and subscription management — replacing platforms that cost six figures a year and still require manual reconciliation every quarter.
Replaces: Maxio, Chargebee, Sage Intacct
Typical legacy cost: £100k+/yr
The Hard ROI of Custom Architecture
A £100k/year legacy CPQ contract doesn't actually cost £100k. When you account for the full picture, Year 1 looks more like this:
£100k — Annual platform license
£60–80k — Implementation agency fees
£50–70k — Internal admin headcount to maintain the system
£20–30k — Lost rep productivity (the "bloat tax": 3 hours/week per rep on clunky workflows)
£250k+ — True Year 1 cost of a "£100k" SaaS contract
Custom AI architecture eliminates the license fee, the agency dependency, and the admin tax. You own the system. There's no renewal negotiation, no vendor lock-in, and no seat-based pricing that punishes you for growing.
Across a typical B2B SaaS GTM stack — CPQ, CLM, billing, forecasting, and the supporting tools around them — companies routinely spend £300k–£500k annually with 30–50% representing pure architectural bloat. That's £100k–£250k returned directly to the bottom line.
Frequently Asked Questions
What is custom AI revenue architecture?
Custom AI revenue architecture is the practice of designing and building bespoke, AI-powered revenue systems — CPQ, CLM, billing, forecasting — that replace legacy SaaS platforms costing £100k+ per year. Instead of buying wrappers around language models bolted onto existing tools, you get purpose-built systems designed around your actual business logic.
How much does custom AI architecture cost compared to legacy SaaS?
A £100k/year legacy CPQ contract typically costs £250k+ in Year 1 when you add implementation agency fees, internal admin headcount, and the productivity tax from clunky workflows. Custom AI architecture eliminates the license fee, the agency dependency, and the admin overhead — returning capital directly to the bottom line.
What legacy platforms can custom AI architecture replace?
Custom AI architecture can replace platforms including Salesforce CPQ, DealHub, Conga, and Subskribe for quoting; Juro, Ironclad, DocuSign CLM, and PandaDoc for contracts; Maxio, Chargebee, and Sage Intacct for billing; and Clari, BoostUp, and Aviso for forecasting.
How long does it take to build a custom revenue system?
Most custom systems are designed and deployed in weeks, not the 6-12 months typical of enterprise SaaS implementations. Because the architecture is built around your actual business logic rather than forcing your processes into a vendor's rigid data model, there is no configuration overhead or vendor lock-in.
Is this just another AI wrapper?
No. Most "AI-powered" RevOps tools are wrappers around language models bolted onto legacy platforms. They add a chat interface to existing dysfunction. Custom AI architecture is purpose-built from the ground up — the AI is the architecture, not a layer on top of it.
Do I need to rip out my entire tech stack?
Not necessarily. The goal is always the right decision for your business. Sometimes that means replacing a six-figure platform with custom architecture. Sometimes it means optimising what you have. Sometimes it means leaving things alone. The assessment starts with understanding where the real cost and friction sit.
Ready to Audit Your Tech Stack?
Let's look at what you're spending, where the architectural bloat sits, and whether custom AI systems could replace six-figure contracts.