Selling an Artificial Intelligence Business

AI software companies usually trade on a mix of growth, profitability, and risk. Multiples tend to be higher when revenue is repeatable, gross margin holds after real inference costs, and you have clean data rights and enterprise-ready security. If revenue leans on pilots or services-heavy implementations, buyers usually price more conservatively. Start with Rejigg’s free valuation calculator, then refine it with customer-level cost-to-serve and pilot-to-production conversion data.

Buyers can be comfortable with third-party model dependency, but they will price supplier risk. Expect questions about how fast you can switch providers, how quality shifts affect your workflows, and what happens to margins if per-token pricing moves. If you can show routing, fallbacks, and usage-based pricing that protects you as customers scale, the dependency usually becomes a manageable diligence item. Rejigg’s secure data room is a good place to share vendor terms and a simple dependency map after NDA.

Yes. You don’t need a broker to sell an AI company, and you don’t need to give up 5–10% of your sale price for introductions and forwarded emails. Rejigg supports a broker-free process: buyers are pre-vetted, NDAs are signed digitally, and you share diligence materials in a secure data room with tight control over access. Start with the finding buyers guide, then list once your diligence package is ready.

For AI, start with the docs that stop deals when they are missing: a customer list tagged by pilot versus production, a data rights map tied to contract language, a cost-to-serve summary that includes inference and cloud drivers, and a security packet that explains where data lives and who can access it. Most technical buyers ask for these early. Rejigg’s preparation guide plus the built-in data room helps you organize it without emailing files around.

Buyers want to avoid a surprise license that forces you to publish proprietary code or limits commercial distribution. Inventory your key dependencies, flag anything with restrictive terms, and document how you comply today. This matters in AI stacks where model serving, vector search, and data pipelines pull in a lot of components. Put the inventory in your data room so the buyer’s technical team can review it quickly during due diligence.

An earnout means part of the price gets paid later if the business hits agreed targets, like revenue, renewals, or customer milestones. In AI, earnouts show up when buyers are uncertain about pilot conversion, retention without the founder, or whether margins hold as usage scales. Earnouts can be fine if the targets are easy to measure and you control the levers to hit them. Rejigg’s deal dashboard lets you compare offers side-by-side, including earnout terms and timelines.

Bring production proof: which workflows run weekly, who owns the outcome on the customer side, and what improved versus the baseline before you went live. Buyers also want to hear how you monitor quality in production and what you do when performance slips, including retraining or rollback. Keep it simple and consistent across customers. Store the reports in Rejigg’s data room so you can share them immediately after NDA.

Working capital is the short-term cash tied up in running the business, roughly what you have coming in soon minus what you owe soon. In AI software, the big swing items are often deferred revenue from prepaid contracts, accrued payroll, and unpaid cloud or model vendor bills. Buyers may ask for a “normal” level of working capital at close so they are not funding old payables on day one. Rejigg’s negotiation guide helps you prep for that ask.

Sometimes, but many AI deals are a tougher fit for SBA because lenders want stable, provable cash flow, and straightforward recurring revenue. If you have consistent profitability, clean books, and low reliance on pilots or founder-led delivery, SBA can work for some buyers. Before you negotiate, model the payment scenarios with Rejigg’s SBA loan calculator so you know what a buyer can afford.

Buyers look at revenue concentration, and in AI they also look at dependency concentration. One customer can matter because they provide unique data, labels, or edge cases that shaped the workflows and evaluation. Losing them can create a quality and roadmap problem, not just a revenue hit. Prepare a customer-by-customer view of revenue, integrations, and what the product would lose if the account disappeared. Rejigg’s data room is built to share that list under NDA with tight permissions.

Human review can be normal in regulated workflows or anywhere mistakes carry real liability. Buyers mainly want clarity on whether review is temporary, permanent, and who pays for it. Show who does the review, how many hours it takes per month, and how that changes as usage grows. If the review cost sits with you, tie it directly to pricing so margin does not compress as customers expand.

Most deals take a few months from the first serious buyer call to close, and longer when data rights, security reviews, or vendor dependencies are unclear. AI processes move fastest when you can share a data rights map, cost-to-serve summary, and security packet immediately after NDA, since technical buyers ask for them early. Rejigg helps with pre-vetted buyers, digital NDAs, and a built-in data room. See the due diligence checklist for timing drivers.

Common problems are contracts that allow processing for one customer but do not allow training across customers, unclear retention and deletion rules, and third-party data licenses that do not transfer on a change of control. Buyers also ask what happens if a customer revokes permission or terminates. The fix is usually straightforward: map each dataset to the actual terms and make sure the product workflow matches the contract. Rejigg’s data room helps you keep those documents organized and share them safely.

Translate cloud spend into customer behavior. Show what it costs to run model calls, store embeddings and logs, and pay any per-request vendor fees, then explain what drives spikes, like long documents, high volume, or low-latency requirements. If you have upside-down customers from early pilot pricing, call them out and show the reset plan. Rejigg’s QuickBooks integration helps you produce clean financials without spreadsheet churn.

No. Seller financing is optional, but it can expand the buyer pool when the business is smaller or when lenders are cautious about AI-specific risks like pilot-heavy revenue or inference-driven margin volatility. If you offer it, tie the structure to what you can verify, like contracted revenue and documented cost-to-serve, and keep clear protections in the agreement. Rejigg’s offer comparison view lets you evaluate seller financing terms against other offers in one place.

Buyers usually want a non-compete so you do not turn around and build the same product, and they want a transition period so knowledge transfer actually happens. In AI, the transition often centers on deployments, model updates, customer escalations, evaluation practices, and vendor relationships. A strong plan names who owns each operational area and what “handoff complete” means. Rejigg’s transition planning guide helps you lay this out in a buyer-friendly way.

Re-trades usually happen when buyers discover AI-specific risk late, like unclear data rights, a hidden services load in onboarding, or gross margins that fall apart once real inference and cloud costs show up at scale. None of that automatically kills a deal, but surprises make buyers look for price protection. The best prevention is to share the hard materials right after NDA. Rejigg supports that with pre-vetted buyers, digital NDAs, and a secure data room.