Preparing Your Software for a Series A Funding Round

The Series A due diligence process has a technical component that most founders underestimate until they're in it. The financial model gets scrutinised. The market size gets debated. And then a VC's technical advisor — or a specialist due diligence firm — gets access to your GitHub repository, your architecture diagram, your infrastructure setup, and your security posture. They have two to three weeks to form a view.

What they're looking for is not perfection. Every early-stage codebase has shortcuts, technical debt, and decisions that made sense at the time but wouldn't be made today. What they're looking for is whether those shortcuts are acknowledged and manageable, whether the architecture can scale to the growth the round is supposed to fund, and whether the engineering team has the discipline and documentation to operate at a larger scale.

What kills deals is not finding technical debt — it's finding technical debt that the founders didn't know about, couldn't explain, or had no plan to address. Surprise is what costs you the round, not imperfection.

This post covers what technical due diligence at Series A actually examines, the specific signals that raise and lower VC confidence, and how to prepare your codebase and documentation before the process begins.

What Technical Due Diligence Actually Examines

The scope of technical due diligence varies by firm and by stage, but the core areas are consistent across almost every Series A process:

The review typically involves: direct repository access (read-only), interviews with the technical founder or CTO, review of infrastructure dashboards, and a review of any prior security audits or penetration tests. Some firms also use automated tools (Snyk, SonarQube, or proprietary scanners) to generate a baseline report on dependency vulnerabilities and code quality metrics.

Code Quality: What Reviewers Look For and What Signals Confidence

"Code quality" in a due diligence context is not about whether the code is beautiful — it's about whether the codebase is maintainable, testable, and comprehensible to engineers who didn't write it. The specific signals:

Test coverage above a meaningful threshold. Zero test coverage is a red flag. Not because untested code is necessarily broken, but because it signals that the team either doesn't value regression safety or was moving too fast to build it in — either of which is concerning at scale. A coverage percentage in the 60–80% range, concentrated on critical paths (payment flows, auth, data processing), is credible. 100% coverage is often a sign of gaming the metric rather than genuine quality.

A consistent style and structure. A codebase where every file looks like it was written by a different person with different conventions — inconsistent naming, mixed paradigms, random folder structures — signals low team discipline or high turnover. A linter configuration (ESLint, Prettier, Rubocop, etc.) enforced in CI and consistent across the codebase signals the opposite.

No hardcoded secrets or credentials. This is caught immediately by automated scanners and is a disqualifying red flag if found. Credentials in code history (even if removed later) are still in the git log. Secrets should be in environment variables or a secrets manager (AWS Secrets Manager, HashiCorp Vault, GCP Secret Manager) — never committed.

Dependency freshness and known vulnerability absence. Outdated dependencies with known CVEs are flagged by every automated scanner. A package.json or requirements.txt full of two-year-old packages with moderate-to-high severity vulnerabilities raises concerns about how the team manages ongoing security hygiene. Run npm audit or equivalent before the process starts and address high-severity findings.

Meaningful commit history. A git log that shows regular, well-described commits across multiple contributors signals a functioning engineering team with process. A git log with one contributor, commits labelled "fix", "fix2", "final", "final_v2" signals a solo-built system that may not be maintainable without its original author.

Architecture: The Scalability Question

The central architecture question at Series A is: can this system handle the growth the round is intended to fund? If the business plan projects 10× user growth in 18 months, the technical reviewer is evaluating whether the current architecture can support that without a full rewrite.

What scalable architecture looks like at Series A:

• Stateless application layer behind a load balancer — horizontal scaling by adding instances, not vertical scaling by upgrading servers
• Database with a clear read/write separation strategy — either read replicas, or a caching layer (Redis) in front of expensive queries
• Async processing for heavy jobs — background queues (Sidekiq, Celery, BullMQ) for anything that doesn't need to block the request cycle
• Observability — structured logging, error tracking (Sentry or equivalent), and infrastructure monitoring (Datadog, Grafana, CloudWatch) with meaningful alerts
• Clear service boundaries — not necessarily microservices, but a codebase where different concern areas are separated enough that they can be extracted or scaled independently if needed

What raises concerns:

• A single database handling reads, writes, background jobs, and analytics — no separation, no ability to scale individual workloads
• No queue system — long-running processes blocking the main request thread
• No caching layer — every page load hitting the database
• No monitoring — engineers finding out about outages from user complaints
• Architecture that requires significant downtime to deploy

The reviewers are not expecting a distributed microservices architecture from a seed-stage company. They are expecting a system with the seams in place to scale — even if scaling hasn't been required yet.

If your codebase was built for speed to market and you're now approaching a fundraise, a pre-Series A technical review with the StartupSphare engineering team will identify the specific issues a VC reviewer will find — and give you time to address them before the process starts rather than during it.

Security and Compliance: The Non-Negotiables

Security gaps are the most reliable deal-killers in technical due diligence, particularly for startups in healthcare, fintech, or any sector handling sensitive personal data.

Authentication and authorisation. Is authentication handled by a reputable provider (Auth0, Supabase Auth, Firebase Auth, Cognito) or a hand-rolled implementation? Hand-rolled auth is not automatically disqualifying, but it receives higher scrutiny — the reviewer will look for PBKDF2/bcrypt/Argon2 password hashing, JWT expiry enforcement, refresh token rotation, and rate limiting on auth endpoints. Missing any of these is a finding.

Data encryption. All sensitive data should be encrypted at rest (database encryption enabled, field-level encryption for PII where required) and in transit (TLS 1.2 or 1.3 everywhere, no HTTP endpoints for any authenticated routes). HTTPS redirects should be enforced at the infrastructure level, not left as a developer discipline.

Secrets management. No secrets in environment files committed to the repository. No API keys in client-side JavaScript bundles. Secrets rotated regularly and with a documented process for emergency rotation if a key is compromised.

Dependency vulnerability management. Automated dependency scanning in CI (GitHub Dependabot, Snyk, or equivalent). A documented process for reviewing and patching high-severity CVEs within a defined SLA.

Prior security audit or penetration test. Not required at Series A, but having one — even a lightweight one from a recognised firm — significantly increases reviewer confidence. The absence of any security review is noted; the presence of one, even if it found issues that were subsequently addressed, signals a security-conscious engineering culture.

For regulated industries (healthcare, fintech, legal), the due diligence also covers compliance posture: HIPAA if handling PHI in the US, SOC 2 if handling enterprise customer data, PCI-DSS if handling card data directly. Not being certified is not disqualifying at Series A — being unaware of the requirement is.

Documentation: The Due Diligence Readiness Signal

Documentation is one of the fastest signals of engineering maturity in a due diligence process, because it tells the reviewer how the team thinks about operational continuity and knowledge transfer. A codebase that only the founding engineer understands is a single point of failure that a VC is being asked to fund at scale.

What documentation should exist before the process:

Architecture overview document. A written description of the system: what components exist, how they communicate, what the data flow looks like, what the infrastructure topology is. This can be a single Markdown document with a diagram — it does not need to be a 50-page specification. It needs to answer "how does this system work?" without requiring an interview with the CTO.

Runbooks for critical operations. How do you deploy? How do you roll back a bad deployment? How do you restore from a database backup? How do you respond to an outage? If none of these are written down, every operational event requires someone with institutional knowledge to be available. That's a bus factor problem.

API documentation. If the product has external or internal APIs (especially if there's a mobile app calling a backend), the API endpoints should be documented — Swagger/OpenAPI spec, Postman collection, or equivalent. Undocumented APIs are opaque to a technical reviewer and suggest the system may be harder to integrate or extend than it needs to be.

Onboarding guide for new engineers. How long would it take a new senior engineer to go from zero to their first merged PR? If the answer is "weeks, because you have to ask X to understand how Y connects to Z," that's a scalability risk for the team, not just the codebase.

Known technical debt register. A documented list of the shortcuts taken, why they were taken, and what the plan is to address them. This is not an admission of weakness — it is evidence of engineering maturity. VCs expect technical debt to exist. They want to see that it's understood, bounded, and managed.

Pre-Series A Technical Readiness Checklist

Before entering a fundraising process:

Code quality:

• CI/CD pipeline in place — automated tests run on every pull request
• Test coverage ≥60% on critical paths (auth, payments, core business logic)
• Linter/formatter configured and enforced in CI
• No hardcoded secrets or credentials — verified with git log search and automated scanner
• High-severity dependency vulnerabilities resolved — npm audit or equivalent clean

Architecture:

• Application layer is stateless and horizontally scalable
• Database has read replica or caching layer for high-traffic queries
• Background job queue in place for async processing
• Structured logging and error tracking (Sentry or equivalent) active
• Infrastructure monitoring with alerts on availability and latency

Security:

• All endpoints served over HTTPS — no HTTP in production
• Auth implemented with a reputable provider or with bcrypt/Argon2 + token rotation
• All PII encrypted at rest — database encryption enabled
• Secrets managed via environment variables or secrets manager — nothing in git
• Dependency scanning automated in CI
• At least one security review completed — even a lightweight one

Documentation:

• Architecture overview document written and accurate
• Deployment and rollback runbook documented
• Disaster recovery and backup restore runbook documented
• API documentation complete (Swagger/OpenAPI or Postman)
• New engineer onboarding guide written — includes local setup and first PR process
• Known technical debt register documented — with severity ratings and remediation plan

IP and ownership:

• All code is owned by the company — no contractor code without IP assignment
• No GPL-licensed dependencies in commercial product without legal review
• Open source libraries used are compatible with commercial licensing

FAQ: Series A Technical Due Diligence

How much notice do we get before technical due diligence starts?

Variable, but typically two to four weeks after a term sheet is signed or when a VC moves from early conversations to serious evaluation. In practice, preparation should start the moment you begin fundraising conversations — not when due diligence is formally announced. A codebase that takes six months to clean up cannot be cleaned up in two weeks before a reviewer arrives.

We have significant technical debt. Does that automatically kill the deal?

No — acknowledged, documented, and planned technical debt does not kill deals. Undiscovered or minimised technical debt does. If a reviewer finds issues you didn't disclose, the credibility damage is often worse than the issues themselves. The best approach: document the debt honestly in a technical debt register before the process, classify it by severity, and prepare a remediation roadmap that shows it can be addressed with Series A capital. Showing you know what's wrong and have a plan to fix it is a strength, not a weakness.

Do we need SOC 2 or ISO 27001 certification for Series A?

Generally not at Series A — these certifications become more important at Series B or when enterprise customers require them as a procurement condition. What matters at Series A is that you can demonstrate security awareness: you know what your sensitive data is, how it's protected, and what your incident response process would be. If your market is healthcare or fintech, investors will look more closely at regulatory compliance posture even at Series A, because the cost of retroactive compliance is a known risk they're pricing.

Our codebase is mostly one person's work. How big a problem is this?

It's a noted risk, not a disqualifying one. The reviewer will flag it as bus-factor risk — if that one person left, how quickly would the system become unmanageable? The mitigating factors are: documentation quality (does the system make sense without that person present?), test coverage (can changes be made confidently by someone new?), and hiring plan (is there a clear plan to distribute knowledge with the Series A capital?). If all three are credible, the bus factor risk is manageable. If the system is undocumented and untested and there's no hiring plan, it's a more serious concern.

Should we hire an external firm to run a pre-due-diligence audit before raising?

Yes — particularly if you haven't had external technical review of any kind before. An independent pre-due-diligence audit gives you the same findings a VC reviewer will find, but three months earlier — when you have time to fix them, document them, or prepare credible explanations. The cost of an external audit is small relative to the cost of a deal falling apart in late-stage due diligence, or closing at a lower valuation because technical risks were disclosed late. Investors who see you've already run an external audit — and addressed the findings — view this as evidence of engineering maturity that reduces their risk.

Technical due diligence is not an obstacle to raising Series A. It is an opportunity to demonstrate that your engineering has kept pace with your business — that the architecture can support the growth you're fundraising for, and that the team has the discipline to operate at the scale the round will enable.

If you're approaching a fundraise and want to know where your codebase stands before a VC reviewer does — the StartupSphare engineering team runs pre-Series A technical reviews that cover every area covered in this post. We deliver a written report, a severity-ranked finding list, and a remediation roadmap you can present to investors with confidence.

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