Technical diligence for AI-native software teams

Know the team before you buy the code.

AlexaGuru gives CEOs, boards, PE firms, and venture investors a decision-grade read on engineering capability: code quality, delivery behavior, AI adoption, key-person risk, and the technical liabilities that do not show up in a pitch deck.

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Built for Private Equity Venture Capital CEOs & Boards CTOs in transition

Engineering Diligence Snapshot

Sample acquisition target

Elevated risk

Architecture 82

Clear modules; two services carry most product risk.

Team Health 76

Strong core contributors; review load is concentrated.

AI Readiness 56

Useful type coverage, weak test pairing in key flows.

Exposure 38

Three exploitable paths need pre-close remediation.

Knowledge concentration is measurable, not guessed: two engineers own 71% of critical-path changes.
Guardian findings mapped to OWASP, NIST, SOC 2, and remediation priority.
CycleTrack history shows delivery velocity improving, but review latency rising.

30+years leading software teams

2purpose-built analysis platforms

100%evidence-backed findings

AIdiligence for the new build model

What we answer

The questions buyers ask too late.

We turn code history, architecture, security exposure, and team behavior into findings an investment committee can act on.

Technical Due Diligence

Architecture risk, maintainability, security exposure, test depth, delivery velocity, and remediation cost - quantified before close.

For PE & VC

Engineering Talent Evaluation

Who carries the work, where knowledge is concentrated, who reviews, who unblocks, and whether the org can scale with the thesis.

For boards & acquirers

CTO Advisory

Practical guidance for leaders navigating AI-assisted delivery, code governance, quality controls, and hybrid human-plus-agent teams.

For CTOs & founders

Evidence engine

Behavior plus code, read together.

Most diligence reads the repository or interviews the team. AlexaGuru connects both: how the team actually works, and what that behavior has produced.

CycleTrack

Behavioral analytics from real delivery history: contribution concentration, review load, delivery archetypes, velocity changes, and AI-adoption maturity.

Guardian

AI-aware semantic code scanning for security, architecture, maintainability, compliance mapping, SARIF export, and agent-readiness scoring.

The deliverable

Built for the IC memo.

Executive summary with go / no-go / proceed-with-conditions framing.
Risk register ranked by materiality, exploitability, and remediation cost.
Team-health evidence with key-person dependency and scaling constraints.
AI-readiness score: how safely agents can understand and modify the codebase.
Follow-on advisory plan for the first 30, 60, and 90 days after close.

Diligence Risk Register Sample excerpt

Finding

Severity

Decision impact

Auth bypass in admin workflow

High

Condition precedent

Review load concentrated in one lead

Medium

Retention risk

Agent-safe structure in core services

Strength

Acceleration upside

Test depth weak around billing flows

Medium

Price remediation

Make the software decision with evidence.

Whether you are evaluating an acquisition, backing a growth round, or taking over an engineering organization, AlexaGuru gives you the technical truth before the decision is irreversible.

Email info@alexaguru.com