The back office has been optimized for thirty years.
The revenue side still runs on instinct.
We work with industrial manufacturers, chemical companies, and financial firms to find the few places AI demonstrably moves revenue, then build the systems that prove it. Marketing, sales, pricing, service: these functions have never been engineered the way the supply chain or the ledger has. AI is the first tool that reads the unstructured information they run on. We have built and deployed it from inside. We know where it moves the number, and where it is theatre.
Everything else in the business has been engineered. The revenue side hasn't.
Finance has its ledger. Operations has its supply chain. Both have been measured, instrumented, and rebuilt over thirty years. The commercial side: brand, sales, pricing, the customer relationship. It still runs on habit, instinct, and a drawer full of tools that don't talk to each other. The largest part of the business no one has properly engineered. Also where the money is made.
AI is the first technology that reads the information this work runs on. Pointed at a defined process (a quoting cycle, an RFP response, a pricing decision, a service queue), it produces gains you can measure within a quarter. Pointed at a vague ambition to "use AI", it scales the existing mess faster. The difference is never the model. It is knowing exactly where in the revenue engine the value sits, and what to change around it.
We have built, priced, sold, and deployed AI inside these functions. Not advised on it from a deck. We can tell you where AI pays and where it doesn't, because we have shipped it ourselves through enough cycles to know. The person who scopes your engagement runs it. Independent of any vendor, measured by one thing: what moves your number.
How you're seen, how you win, how you keep it.
Three connected parts of the same practice. Most engagements start in one and pull in the rest: the message, the deal, the price, and the service are the same conversation seen from different sides.
Be the name the market already trusts.
Before a buyer calls, they've already decided. We make sure they decide in your favour: the commercial position, the narrative, the website, and the AI-search footprint that determines whether they call you or a competitor. The work that makes every later commercial conversation shorter and warmer.
- Commercial positioning and the narrative buyers believe
- A B2B website engineered to convert, not just to look right
- AI-search presence: getting named when buyers ask an assistant
Win more of the deals you are already in.
The commercial motion from first inbound to signature: how leads get answered, how deals get qualified, how proposals and quotes get out the door. Where AI moves the number (quote turnaround, RFP win rate, speed-to-lead) we build it into the process you already run, not a tool beside it.
- A go-to-market motion that fits how you actually sell
- RFP and quote cycles: out faster, won more often
- Speed-to-lead and deal intelligence, inside your CRM
Capture the value. Then keep it.
The part most firms leave on the table: what you charge, and whether the customer stays. Pricing logic that holds in the room, and an after-sales motion (service, renewal, expansion) designed so a won account compounds instead of quietly leaking. AI where it earns its place: triage, patterns, and the signals that flag a leaving customer before they go.
- Pricing strategy, and the discipline to hold it in the deal
- After-sales and service designed to retain and expand
- Churn signals and service triage that compound the account
Where the number actually moved.
Built for industrial and regulated B2B.
Not every AI engagement is ours to take. The ones that are share a pattern: complex sales, long deal cycles, and a commercial operation that has never been properly engineered.
Industries
Company profile
What usually triggers an engagement
- Quote or RFP turnaround is losing deals to faster competitors
- AI has been bought or piloted and isn't moving revenue
- Pricing is left to instinct — discounting is habit, not strategy
- Churn is only visible at the renewal date
- Entering a new vertical with the wrong commercial narrative
If the situation sounds familiar, the diagnostic conversation is where we start — not a proposal.
What people usually ask before the first conversation.
What does Raining Code do?
We apply AI to the revenue engine of a B2B or industrial company — how you are seen and found, how you sell, what you charge, and how you keep the customers you win. We have built, sold, priced, and deployed AI inside these functions ourselves, so we know where it moves the number and where it is theatre. Senior-partner-led, independent of any tool.
Can AI actually improve sales win rates?
Yes — where it is pointed at a defined process rather than a vague ambition to 'use AI'. The reliable gains are in quote turnaround, RFP response speed and quality, speed-to-lead on inbound, and deal qualification. One specialty chemicals client went from five-day quotes to eleven hours and lifted RFQ conversion 26%. Pointed at no particular process, AI just scales the existing mess faster.
Should we buy an AI sales tool or build our own?
It depends on the process — and getting that decision right is the work. We are independent of any vendor, so the answer is buy, build, or partner on the merits, not whatever we resell. For a narrow, common step, a tool usually wins. For a process that is core to how you compete, configuring or building tends to pay back. We map it before anyone spends.
How do we get our company recommended by ChatGPT and other AI assistants?
Buyers now ask AI assistants for vendor shortlists before they visit your website, and the assistants answer from everything you have published. Answer engine optimization makes sure what they return about you is accurate, authoritative, and consistent with the position you want to hold. It is part of the brand and demand work — and it is fast, usually a few weeks.
How can AI reduce customer churn and improve retention?
After the deal closes, AI earns its place in the signals: patterns that flag an account about to leave before a human notices, service triage that routes and answers faster, and the expansion cues that turn a won customer into a growing one. Most firms leave this value on the table because no one engineered the after-sales motion the way they engineered the pitch.
Who advises on AI for go-to-market in industrial and B2B companies?
Raining Code does — senior-partner-led across Europe and North America, Rohit Chikballapur in Basel and Adi Sankaran in Houston. We work with firms that sell complex, deal-driven products: manufacturing, components, specialty industrials, energy, infrastructure, B2B software. The people advising you have run the go-to-market motion and deployed AI into it themselves.
We built the practice we would have hired.
Operators in brand, sales, and delivery, who brought AI into it where it paid. A senior partner in your market, the full bench behind them.
Adi Sankaran owns how you win. He led product for an AI-native field service platform at Zinier, shipped to enterprise operators worldwide, and is that rare product leader who understands sales from the inside. His domain is the deal cycle: where AI genuinely moves a sale, and where it is decoration.
Sushobhan Mukherjee owns how you are seen and found. Thirty years in brand strategy: AVP Digital Design and Strategy at Infosys, a Grand Effie and a Jay Chiat Award, a media company he co-founded acquired by the Financial Times. His benchmark is whether the work converts, including whether AI assistants name you when buyers ask.
Rohit Chikballapur owns how you keep what you win. Seven years building and deploying industrial AI at Facterra across DACH and French plants. The pricing, service, and after-sales motion that decides whether an account compounds or quietly leaves.
Meet the practice