# Build vs buy for pricing software > An honest comparison of building pricing tooling in-house against buying it, for manufacturers and distributors without a dedicated pricing team. Source: https://revomo.ai/build-vs-buy/ --- Build vs Buy ## Yes, you could build it. The question is whether it keeps up. AI has turned the first version of almost anything into a weekend project, which makes “just build it” the most tempting it has ever been. But commercial decision intelligence isn’t the demo on top; it’s the integrated architecture underneath, from security and governance to the feedback loops that learn from every deal, on a bedrock of twenty years of doing this at the largest companies on earth. This is the build-vs-buy call every CIO, CTO, CFO and CEO is now making. Compare the approaches[See Revomo in action](https://revomo.ai/contact/) A decision layer, not a dashboard Rides the AI frontier Governed, not a science project 80% Of the build is the part no demo shows Years Of margin domain logic, already encoded Every release The frontier improves, so does Revomo Weeks To live value, not engineer-years The case in 20 seconds #### AI made the demo cheap. It didn’t make commercial decision intelligence cheap. - **The dilemma.** Rapid AI cycles make “just build it” more tempting than ever, but the demo on top is a tenth of the work. - **The depth.** The value is the integrated architecture below the line, from security & governance down to the feedback loops that learn from every deal. - **The edge.** It is built by a team with two decades of scars and successes delivering this to Fortune 500 and Global 2000, and it compounds as the AI frontier moves, while a one-time build freezes. The team behind it 20+ yrs building pricing & margin intelligence F500 / G2000 where these systems were forged, at scale One focus this problem is our entire R&D A different job ### Your stack is excellent, at a different job A spreadsheet holds a number. A BI layer shows you the past. A data-prep tool moves and cleans data. An ERP records the transaction. Orchestration shuttles data between systems. Each is genuinely good at what it does, and none of them was built to **decide the next margin-protecting move at the moment of the deal**. That is the entire job of commercial-margin intelligence. Spreadsheets hold the number BI & dashboards show the past Data prep / ETL move & clean data ERP module record the transaction Orchestration shuttle data around Revomo decides & governs the margin What the job actually requires ### What it takes to run margin on one spine Eight capabilities separate a report from a governed decision. Pick the approach you have today and see how far it gets, and what you would still own and maintain. The dilemma, in one picture ### AI builds the tip. The iceberg is the rest. Rapid AI cycles make the visible part (a dashboard, a price screen) a weekend project. Commercial decision intelligence is the integrated mass below the line: from **security and governance** down to the **feedback loops** that learn from every deal, resting on a **bedrock of two decades** delivering this to the largest companies on earth. Tap a layer. The tip is roughly a tenth of the work. Everything below the line, and the twenty years behind it, is what “just build it” quietly signs you up for. Tap any layer. When building *is* the right call To be clear: if commercial pricing intelligence **is** your product, the thing your customers pay you for, then build it, and we will cheer you on. For everyone else it is undifferentiated heavy lifting: a system you would operate but never sell. Buy that, and point your scarce engineers at what only your company can build. “We’ll build it with AI” ### A frontier model is horizontal. Margin is vertical. Point a general model at your data and you get a brilliant generalist with no idea how *your* price, discount, promotion, rebate, contract and cost interact, and a habit of inventing numbers, which is fatal on financial decisions. The value was never the model. It is the governed inference layer on top of it. **Governed margin decisions** priced, guided and protected at the point of every deal ↑ **The Revomo inference layer** built for commercial margin Governed margin spine Domain priors Decision corridors Optimization Explainability & lineage Closed loop to execution ↑ **Frontier AI models** horizontal, commoditizing, improving every month: Revomo rides the best of them This is why the gap only widens. Revomo rides every frontier leap **and** compounds its margin domain layer across every customer. A homegrown build is frozen the day it ships, and the frontier does not wait. Revomo Homegrown build Steady frontier Fast frontier Today Year 1 Year 2 Year 3 The day you ship v1, Revomo has already shipped its next model generation. Tap a year on the chart. One decision, four seats ### Why the whole C-suite lands in the same place Build vs buy is rarely one person’s call. It keeps resolving to Revomo because each seat optimizes for something different, and the iceberg answers all four at once. ##### CEO, strategy & focus Margin is a board-level lever and engineering is scarce. Point your builders at what differentiates the company; buy the intelligence that doesn’t. ##### CFO, return & risk Recovered margin lands in EBIT in weeks, at a fraction of a multi-year build, and every number is defensible to the board, not a sunk-cost science project. ##### CTO, architecture & depth Knows the real system is the layers below the line, not the demo, and that a part-time build can’t keep pace with a team whose whole frontier is this. ##### CIO, integration & governance Warehouse-native, SOC 2, SSO, audit and lineage out of the box, no new system to secure, integrate and maintain forever, and no key-person risk. The bedrock ### Built by people who already have the scars The layers below the waterline aren’t a spec you can prompt into existence. They are the residue of two decades building commercial decision intelligence for Fortune 500 and Global 2000 companies, where the failures taught the guardrails as much as the wins proved the model. 20+ Years building pricing & margin intelligence F500 / G2000 Where these systems were forged, at real scale Scars + wins The failures that taught the layers, not just demos One focus This problem is our whole R&D, not a side project You can hire brilliant engineers and point the best models at the problem. What you cannot shortcut is twenty years of knowing *which* layers matter, *where* margin actually hides, and *what* breaks in production at a global manufacturer. That experience is the bedrock under every recommendation, and it ships with Revomo on day one. The bottom line ### Build is a project. Margin is a frontier. You can absolutely build a v1. The question a commercial leader has to answer is whether a part-time internal project keeps pace, year after year, with a company whose entire purpose is this. ##### Weeks to value, not engineer-years ##### Maintained & improving, not frozen at build ##### Governed & auditable, not a black box ##### Rides the frontier, not chasing it part-time ##### Your team on your product, not commodity infra ### Don’t bet your margin on a backlog Run a side-by-side: a focused Revomo pilot against whatever you’d build. Same data, same deals. See which one is protecting margin in weeks, and which one is still in sprint planning. [See Revomo in action](https://revomo.ai/contact/)[See the ROI](https://revomo.ai/why-revomo/) FAQ ### The build-vs-buy questions, answered Our data and business are unique, doesn’t that favor building? Your data is unique; the *problem* (price-to-pocket leakage, rebate accruals, deal corridors, elasticity) is not. Revomo configures to your hierarchies, rules and corridors out of the box. You get the uniqueness without rebuilding the 80% that’s common to every manufacturer. We already own Power-BI-class tools and a warehouse. Why pay again? Keep them: Revomo sits on top of them. A warehouse stores data and a BI layer reports it; neither decides the next margin-protecting price at the moment of the deal, governs it, or improves itself. That decision layer is the part you’d still be building. Won’t AI make a tool like this trivial to build soon? AI keeps making the *demo* easier, for everyone, us included. The durable work is the governed data model, the decision corridors, the explainability, the integrations and the maintenance as the frontier moves. Revomo rides every model improvement and compounds that domain layer; a one-time build can’t. How long would building this actually take us? A convincing prototype, weeks. A governed system you’d trust to price real deals (data model, entity resolution, guardrails, integrations, security, change management) is typically many engineer-years, then ongoing headcount to keep it alive. Revomo pilots in weeks because that work is already done and hardened. If we adopt Revomo, are we locked in or losing control? The opposite. Your data stays in your warehouse, every decision traces to a governed record you can export, and the corridors and rules are yours to set. You control the policy; Revomo runs the intelligence, and frees your engineers to build what actually differentiates you. What if we outgrow it, or want to bring it in-house later? Revomo scales from a single pilot to the full portfolio at enterprise throughput, so most teams grow into it rather than out of it. Your governed records, lineage and history are yours and exportable, so you are never holding a black box you can’t reason about.