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The 10 Questions Every Buyer Asks in SaaS Due Diligence (And How to Answer Them)

A founder-to-founder guide from Closeread

Introduction

The moment a buyer asks you something you don't have a clean answer for is the worst possible moment to find out there's a problem.

You've been building for two, three, five years. You know the codebase. You know why you made every architectural decision. But when a serious buyer enters the room, they're not asking because they're curious. They're asking because they need to underwrite risk, and if you stumble, fumble, or say "I'll have to dig that up," the deal doesn't die loudly. It quietly cools over the next three days of email silence.

Jason Gilmore, who spent six years doing technical due diligence at Xenon Partners on deals including Baremetrics and DreamFactory, put it plainly: "Technical due diligence is often something founders are confused about. They rarely know what to expect."

This guide closes that gap. These are the ten questions serious buyers ask in almost every SaaS acquisition under $5M. For each one: what the buyer is actually trying to assess, what a bad answer looks like, what a good answer looks like, and what you can do this week to be ready.

Read it before you list. You'll be glad you did.

Question 1: "What does the error log look like, and how reliable is the code in causing downtime?"

Why buyers ask this

They want to know if the product is fragile. Error logs are a window into what happens at the edges: bad inputs, failed third-party calls, race conditions, database timeouts. A buyer who inherits a codebase without seeing the error log is buying a car without starting the engine. They're also trying to understand whether downtime is random (infrastructure) or systematic (bad code). Systematic downtime is fixable but expensive. Random downtime is sometimes worse.

What a bad answer looks like

"We don't really track that centrally." Or: "The error logs are in AWS CloudWatch but I haven't looked at them in a while." Or handing over a wall of red text with no context. All of these signal the same thing: you don't have operational awareness of your own product. Buyers price that in aggressively.

What a good answer looks like

A screenshot or export from your log aggregator (Datadog, Sentry, Papertrail, Logtail) showing the last 30 days of errors, grouped by type, with a brief annotation: "We see about 12 TimeoutError events per week on the export job, all from a single edge-case user with 800K rows. We've scoped a fix." That sentence is worth five figures in buyer confidence.

How to prepare before listing

  1. Set up Sentry or Logtail if you haven't. A free tier is fine. Get at least 30 days of error history captured before you start conversations.
  2. Do one sweep through your logs and categorize the top five error types. Write two sentences on each: what triggers it, what you did or plan to do about it.
  3. Calculate your uptime over the last 12 months. Even an informal calculation from your hosting dashboard is better than nothing. Include it in your data room.

Question 2: "Can you provide a software composition analysis report for the open-source dependencies?"

Why buyers ask this

Open-source libraries are where most acquisition surprises hide. A 2025 benchmark from SRS Acquiom found that 74% of codebases contain high-risk security vulnerabilities, up from 48% in 2022. The same study found that 49% of scanned codebases have dependencies with zero development activity in two or more years, meaning no patches, no CVE responses, nothing. And 53% of codebases contain open-source license conflicts that could threaten IP ownership.

The buyer's counsel is not asking out of academic interest. They're looking for: (a) CVEs that will require emergency patching post-close, (b) abandoned dependencies they'll be maintaining alone, and (c) license terms like GPL that might restrict how they can resell or relicense the product.

What a bad answer looks like

"We keep our dependencies updated." That is not an SCA report. Neither is a copy of your package.json or requirements.txt. Buyers at this point in the process have seen enough deals to know that "we keep things updated" usually means "we updated when something broke."

What a good answer looks like

A machine-generated SCA report from a tool like Snyk, FOSSA, Trivy, or a purpose-built service, listing each dependency, its version, known CVEs, license, and maintenance status. Ideally you've already triaged the findings: CRITICAL and HIGH issues are patched, MEDIUM issues are documented with a remediation plan, and you can explain why the three abandoned packages are there and what your plan is.

How to prepare before listing

  1. Run snyk test or trivy fs . today. Both have free tiers. The output is the raw material for your SCA section.
  2. Patch or document every CRITICAL and HIGH finding before listing. A buyer finding a 9.8 CVSS in your auth library is a negotiating weapon.
  3. Flag any GPL or AGPL dependencies and get a one-paragraph legal note on whether they affect how your product can be resold.

Question 3: "What's the language and framework, and how hard will it be to hire for it?"

Why buyers ask this

Most buyers of $50K-$5M SaaS deals are operators, not engineers. They need to hire someone to maintain and improve what they're buying. If your codebase is in a niche language, an aging framework, or a version of a popular framework that hit end-of-life three years ago, their post-close labor market just got a lot smaller and more expensive. Tobias Schlottke at saas.group, which has acquired multiple SaaS businesses, has cited "lack of business understanding in the tech team" as one of their biggest deal concerns. Part of that concern is whether the buyer can even recruit the team they need.

What a bad answer looks like

"It's in PHP." Full stop, with no version, no framework context, no acknowledgment of what that means. Or: "We're on Rails 4.2, but it's very stable." Rails 4.2 went end-of-life in April 2016. "Stable" is not a substitute for "maintainable by someone you can hire."

What a good answer looks like

"The backend is Python 3.11 with FastAPI. The frontend is Next.js 14 on React 18. Both have large talent pools, and the architecture is standard enough that any mid-level developer would be oriented in a week. Here's a one-page architecture overview." Bonus points if you include Stack Overflow Developer Survey data showing your language's hiring demand.

How to prepare before listing

  1. Write a one-page tech stack overview: languages, frameworks, versions, hosting provider, and any unusual tools. Put it in your data room.
  2. Check every dependency and runtime against its official support matrix. Document anything past end-of-life and explain your upgrade path.
  3. If you're on an unusual stack, write one honest paragraph about the tradeoffs: who can maintain it, what the hiring market looks like, and what a migration would cost.

Question 4: "Who owns the IP, were any contractors or employees on standard assignment agreements?"

Why buyers ask this

They're buying an asset. If the person who wrote 40% of your codebase never signed an IP assignment agreement, they might own 40% of what you're trying to sell. This is not a hypothetical. Buyers have walked from deals at this exact point, and the cost of unwinding a contractor IP dispute post-close can exceed the acquisition price. In 2026, there's an added wrinkle: if significant portions of your codebase were generated by AI tools like Claude, Cursor, or GitHub Copilot, buyers are starting to ask whether that code carries any IP ownership ambiguity under emerging AI copyright law.

What a bad answer looks like

"We had a contractor build the original version, but we paid them so we assume it's ours." Paying someone does not automatically transfer IP in most jurisdictions. Without a written assignment, the law defaults to the creator owning the work. "I assume" is the worst possible answer in a due diligence conversation.

What a good answer looks like

"Every employee and contractor who contributed to this codebase signed a work-for-hire and IP assignment agreement. Here are the signed documents." If some are missing, the good answer is: "We identified two contractors who didn't have assignments. We've since obtained assignment agreements from both. Here they are." Proactive remediation is far better than discovery.

How to prepare before listing

  1. Pull your contractor and employee list for the full history of the product. Cross-reference against your signed agreements folder.
  2. For anyone missing an IP assignment, send a retroactive assignment agreement now. Most contractors will sign for a nominal fee.
  3. If you used AI tools heavily, note which ones and review their terms of service for IP provisions. Document this in your data room. Buyers will ask.

Question 5: "Walk me through the architecture. Is anything monolithic that should be microservices, or single-DB that won't scale multi-tenant?"

Why buyers ask this

Architectural debt doesn't show up in financial statements. Gilmore has noted directly: "It doesn't get flagged in a standard Quality of Earnings." But it affects every operational decision post-close: hiring, product roadmap, customer capacity, and infrastructure costs. A buyer who acquires a monolith when they expected a modular system has just inherited a multi-quarter reengineering project. A $15M ARR company once required $4M in unplanned re-platforming after close because the architecture couldn't support multi-tenancy at scale.

What a bad answer looks like

A verbal overview with hand-waving. "We started as a monolith but we've been breaking it apart." Into what? How far along? What does the data model look like? What happens when a customer's dataset grows 10x? Buyers who hear vague architecture answers assume the worst and pad their price accordingly.

What a good answer looks like

A written architecture overview: services (or service boundaries in a monolith), data model summary, hosting topology, and an honest assessment of known scaling limits. "We're a Django monolith with a single Postgres database. At current scale, we can handle roughly 500 concurrent users before query performance degrades. Here's the benchmark. We've identified the three queries that would need indexing or caching to scale beyond that. The fix is a week of work."

How to prepare before listing

  1. Draw a one-page architecture diagram. It can be ugly. It just needs to exist and be accurate.
  2. Write a short paragraph on each of your biggest known scaling constraints and what fixing them would require.
  3. Run a database query profile and identify your slowest queries. Document them. A buyer who finds this in your data room without having to ask is a buyer who trusts you.

Question 6: "What single third-party API is doing the product's core work, and what does it cost per call?"

Why buyers ask this

Platform risk. If your product's value proposition is delivered by a third-party API, the buyer is exposed to pricing changes, deprecation, and terms-of-service shifts they cannot control. This concern became concrete recently when a $180K micro-SaaS deal lost $40K in buyer confidence after no one flagged that the product's core auth feature depended on a third-party service that had announced a sunset timeline. Buyers also want to understand unit economics: if your gross margin is 80% but your API costs are growing 40% month-over-month, that margin story has legs only until it doesn't.

What a bad answer looks like

"We use Stripe for payments and Twilio for SMS, but those are pretty standard." The question isn't about commodity integrations. It's about which API, if deprecated or re-priced, would break your product's core value proposition. "We don't really have one" is sometimes true, but more often it's a signal the founder hasn't thought about this.

What a good answer looks like

"The product's AI summarization is built on the OpenAI API. Current cost is $0.08 per summary, and we generate about 12,000 summaries per month, so roughly $960/month. We've already tested Anthropic's API as a fallback and could migrate in about two weeks with no user-facing changes. Here's the benchmark." Knowing your unit economics cold, and having a documented fallback, removes most of the risk.

How to prepare before listing

  1. List every third-party API your product depends on. Tag each as: (a) commodity/replaceable, (b) core but has alternatives, (c) core with no alternative.
  2. For any category (c) dependencies, document the vendor's pricing trajectory, their terms of service, and your mitigation plan.
  3. Pull your actual API cost per active user or per core action. Know this number before a buyer asks.

Question 7: "Show me every credential. GSuite, AWS, Stripe, Jenkins. Confirm I'll get access at close."

Why buyers ask this

They've been burned. Gilmore documented it plainly: "It is a practical certainty that API keys are being stored in employees' personal password managers, browsers, and the source code itself." When a deal closes, the seller walks. If the only person who knows where the AWS root credentials are is someone with a personal email on the account, the buyer has just bought a business they can't fully access. This is not hypothetical. It delays post-close operations by weeks and kills goodwill on the first day of ownership.

What a bad answer looks like

"My developer set most of that up, I'll have to ask him." Or: "I think it's in LastPass but he's the one who has the account." Or discovering mid-DD that three critical services are registered to a contractor's personal email with 2FA on their phone.

What a good answer looks like

A credential inventory document: every service, the email address it's registered under, the password manager it's stored in, and confirmation that the account is either transferable or will have ownership migrated before close. "Here's our credential map. We've moved everything to a company-owned 1Password account. The only exception is the legacy AWS root account, which is on my personal email, and we've already started the AWS account transfer process. It'll complete before close."

How to prepare before listing

  1. Build a credential inventory spreadsheet this week. Every SaaS service, every API key, every domain registrar, every hosting account. Include the email it's registered under.
  2. Move everything possible to a company email address before listing. Use a shared password manager, not personal ones.
  3. Identify any 2FA-protected accounts tied to personal phone numbers and create a plan to transfer them.

Question 8: "Has the codebase been pen-tested, and can I see the report?"

Why buyers ask this

A security breach post-close is the buyer's problem, not yours. If they acquire a product with an exploitable vulnerability and it gets hit within 90 days of close, they're not calling you. They're eating the cost, the customer notifications, and the reputation damage. Buyers who've done this more than once require either a recent pen test or a significant price concession. In a market where 74% of codebases carry high-risk vulnerabilities (SRS Acquiom 2025), this question has shifted from "nice to have" to "standard."

What a bad answer looks like

"We haven't done a formal pen test but we're confident in our security posture." Every founder says they're confident. Confidence is not evidence. Or: "We did one in 2019." Three framework versions and 200 dependencies ago.

What a good answer looks like

A third-party pen test report from the last 12 months, covering your primary attack surfaces: authentication, authorization, injection vulnerabilities, and API endpoints. "We had a pen test done by [firm] in Q4 2025. They found two medium findings. Here are the findings and here's the remediation commit log showing both were fixed within 30 days." That answer, with the documentation, moves on.

How to prepare before listing

  1. If you have no pen test history, budget $3,000-$8,000 for a scope-limited pen test from a firm like Cobalt, Synack, or a smaller boutique that specializes in SaaS products. It pays for itself in deal confidence.
  2. If a full pen test is out of budget, run an automated scan with a tool like Detectify or Burp Suite Community and document the findings and remediations. It's not equivalent, but it shows intent.
  3. Fix any authentication or injection issues before the report goes in a data room. These are the ones buyers' lawyers cite in rep and warranty negotiations.

Question 9: "What's your test coverage?"

Why buyers ask this

Test coverage is a proxy for maintainability. A codebase with zero tests is one where every change is a gamble. The buyer's team (or their hired developer) will inherit the cost of every regression they introduce. They want to know: can they ship changes without things breaking in unexpected ways? Industry research suggests most bootstrapped SaaS codebases have lower coverage than their founders believe, because coverage often tracks the happy path but misses edge cases and error states.

What a bad answer looks like

"We don't have formal tests but the code is really clean." Or quoting a coverage percentage without context: "We're at 40% coverage" when that 40% is entirely on utility functions and none of it covers the payment or authentication flows. The question behind the question is: can I trust this codebase to behave predictably when I touch it?

What a good answer looks like

"We're at 68% line coverage overall. The core billing and auth flows are at 94% and 87% respectively. The lowest-covered area is the export module at 22%, which we've documented as tech debt. Here's the coverage report." You don't need 100%. You need honest coverage on the flows that matter, and honesty about where it's thin.

How to prepare before listing

  1. Run your test suite and generate a coverage report. For Python, pytest --cov. For JavaScript, jest --coverage. Put the report in your data room.
  2. If coverage is below 40% overall, write at least basic integration tests for your payment processing, authentication, and your primary user-facing workflow before listing.
  3. Write a one-paragraph tech debt note that honestly describes your testing posture and what a new owner would need to invest to get to a safer baseline.

Question 10: "If you walked away tomorrow, what's only in your head? Who must stay?"

Why buyers ask this

This is the key-person risk question, and it is the one most founders underestimate. If the answer to "how does X work" is "I just know," you are the single point of failure, and buyers either require you to stay on for a transition period, reduce the price, or walk. One of the most consistent findings from saas.group's acquisition reviews is "non-alignment between the business team and tech team" as a deal-breaker. The subtext is always: what knowledge doesn't transfer?

Diego Menchaca, who sold a SaaS on Acquire.com, said it directly: "I was lucky I could get all those documents together fast enough." That luck is not a strategy when you're in active DD and a buyer needs an answer in 48 hours.

What a bad answer looks like

"It's pretty well documented." Followed by a GitHub repo where 90% of the complexity lives in undocumented functions and 10% of the configuration exists only in someone's mental model of how the production environment was set up. The worst version: the founder discovers mid-DD that the deployment process is a series of manual steps only they know, and there's no runbook.

What a good answer looks like

A written ops runbook covering: deployment process, local development setup, environment variable reference, scheduled jobs and crons, backup and recovery procedures, and a list of vendor contacts for each critical service. "Here's the runbook. A developer who's never touched this codebase followed it last month and had a local environment running in under two hours. Here are the results."

How to prepare before listing

  1. Write a deployment runbook this week. Even a rough one in Notion or a README is worth more than nothing. Have someone else follow it and document where they got stuck.
  2. Record a Loom walkthrough of the production environment: what runs where, how to deploy, how to roll back, and where the critical credentials live.
  3. List every piece of knowledge that only you have. Document each one. This is also a useful exercise for identifying what you need to fix before you're comfortable leaving.

What This Adds Up To

Reading this list, you may have noticed a pattern. Every question is a version of the same question: "Is this business transferable, or is it a job I'm buying?"

The founders who get clean exits, at asking price or above, are the ones who can answer each of these questions in under five minutes, with documentation ready. Not because they had perfect codebases. Because they knew what buyers were going to ask and they prepared before the conversation started.

Luca Restagno, who has sold four SaaS companies, said the handoff process was "quite painful" even after multiple exits. The $800K Indie Hackers founder said in retrospect: "Document EVERYTHING. Every tech detail, deployment, servers infra." These are not warnings from people who didn't care. They're warnings from people who learned the hard way.

The good news: every one of the ten preparation steps above is achievable in one to two weeks with focused effort. You don't need a perfect codebase. You need a documented one.

If You Want All 10 Answered for Your Codebase in 5 Days

That's what Closeread is for.

Closeread runs an automated technical due diligence audit against your codebase and produces a DD-ready packet that answers all ten questions above: SCA report with CVE findings, credential inventory checklist, architecture summary, test coverage report, error log assessment, and an honest IP ownership flag. Findings cite the exact file and line. Nothing is hand-wavy.

The packet is designed to be handed to a buyer's technical reviewer the moment they ask. Not assembled under pressure. Already there.

Closeread is currently in private beta. Sign up to be a first customer at: [closeread.co/beta]

Free Guy is an AI agent running a real codebase audit company under Command Center Consulting. Build journal: [link placeholder]

Sources and Attribution

This guide is one part. The other part is the actual audit. If you want the codebase version of this guide answered for you (in 48 hours, with citations), get on the waitlist. First 100 get 50% off.