GTM Due Diligence Brief Pack — AI Offer → Evidence-Led Marke

    1

    GTM Due Diligence Brief Pack turns supplied evidence about an AI product, agent, or SaaS offer into a practical review for a clear next step.

    $12

    Secure checkout via Stripe

    30-day refund guarantee

    Converts to your local currency at checkout

    0 installsSecurity scanned

    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseOpenClawOpenClaw+21 more

    GTM Due Diligence Brief Pack — AI Offer → Evidence-Led Marke

    Example session with this skill installed

    offer: Enterprise Retrieval-Augmented Generation (RAG) platform
    decision_question: Proceed to a paid POC or build an internal solution?
    audience: CTO and Engineering Lead
    evidence: Technical documentation, security whitepaper dated Oct 2023, and internal cost estimates for a 3-month build.
    alternatives: Internal LangChain-based prototype.

    • Read your context and instructions
    • Compiled the gtm due diligence
    • Generated the document

    One or two lines summarising what was done.
    A due-diligence brief was generated comparing the enterprise RAG platform against an internal build, focusing on security evidence and engineering trade-offs.

    GTM due-diligence brief: Enterprise RAG Platform

    Decision question: Proceed to a paid POC or build an internal solution?
    Audience / decision owner: CTO and Engineering Lead
    Market scope: Enterprise internal knowledge management
    Evidence boundary: Tech docs, Oct 2023 Security whitepaper, internal build estimates
    Generated: 2024-05-20 · Draft for human verification — not investment advice or a forecast

    1. Executive readout

    • What appears supported: SOC2 Type II compliance [E2]; Out-of-the-box connectors for Jira/Confluence [E1].
    • What is a hypothesis: Vendor claims of <200ms latency at scale remain unverified in supplied docs.
    • Most decision-relevant risk: Provider lock-in due to proprietary vector index format.
    • Recommended next step: Run a 1-week latency stress test on the vendor's sandbox.
    • Confidence: medium

    2. Offer and decision frame

    • Job to be done: Queryable internal documentation for 500+ engineers.
    • Primary user / buyer: Engineering teams.
    • Stated promise: Zero-config RAG with enterprise-grade security.
    • Workflow and human hand-offs: Automated indexing; manual citation verification by users.
    • Decision options in scope: test | buy | build

    3. Evidence ledger

    IDClaim or observationSource / dateTypeConfidenceDecision implication
    E1Supports 15+ data connectorsTech DocsReportedhighReduces initial integration effort
    E2SOC2 Type II CompliantWhitepaper (Oct 23)ObservedhighMeets baseline procurement safety
    E3Internal build takes 3 monthsInternal EstAssumedmediumBaseline for ROI comparison

    4. Market and alternative context

    • Category / problem space: Enterprise Search / AI Knowledge Management
    • Alternatives: Internal build (LangChain/Pinecone), manual wiki search.
    CriterionOfferInternal PrototypeEvidence / confidence
    Time-to-value1 week (config)12 weeks (build)High
    CustomizabilityLow (Black box)High (Full control)Medium
    SecurityVerified SOC2Requires auditHigh

    5. AI, operational, and commercial risk review

    Risk areaEvidence observedUnknown / failure modeImpact if trueVerification
    Data / privacyEncryption at restData residency optionsHighReview DPA
    Lock-inProprietary indexMigration costMediumAsk for export API

    6. Positioning and GTM hypotheses

    Positioning hypothesis: For CTOs who need secure internal AI search, this platform is a turnkey RAG solution that eliminates build-time, unlike internal prototypes, because it provides pre-built security compliance.

    • Disqualifiers: Teams requiring custom embedding models not supported by the vendor.

    7. Priority open questions

    PriorityQuestionWhy it changes decisionEvidence needed
    1What is the cost per query at 10k queries/day?Affects long-term OpEx vs buildPricing sheet

    8. Validation plan

    PriorityHypothesisSmall, reversible testSignal to observe
    1Latency stays <500msLoad 1000 docs to sandboxResponse time logs

    Next steps

    • Request the latest Data Processing Agreement (DPA) from the vendor.
    • Schedule a technical deep-dive on vector index portability.
    • Baseline the current "time-to-answer" for developers using manual search.

    gtm-due-diligence-brief-pack-ai-offer-ev.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Audit AI vendor claims using structured evidence instead of marketing fluff.Assess data privacy and operational risks for new SaaS integrations.Design small validation tests to verify product-market fit before scaling.Compare internal build costs against third-party AI service offerings.

    About this skill

    GTM Due Diligence Brief Pack turns supplied evidence about an AI product, agent, or SaaS offer into a practical review: decision frame, evidence ledger, market and alternative context, AI/operational risk review, positioning hypotheses, open questions, and small validation tests. It is built for founders, product teams, GTM operators, buyers, and consultants who need a clear next step—not invented market metrics, investment advice, or outcome guarantees.

    What it covers

    • Market context, buyer/job, category, alternatives, and buying friction
    • Evidence quality with observed / reported / inferred / unknown labels
    • AI capability, evaluation, privacy, security, reliability, dependency, and adoption questions
    • Positioning, proof gaps, objections, and GTM hypotheses
    • Prioritised open questions and reversible validation tests
    • A decision checkpoint that states what the evidence does and does not support

    Honesty and boundaries

    This is a process and template skill. It uses supplied evidence and labels uncertainty; it does not browse by default or invent customer counts, market size, accuracy, uptime, savings, ROI, revenue, or other metrics. It is not investment, financial, legal, security, privacy, or compliance advice, and it does not guarantee product performance or commercial outcomes.

    Brand: Cygnix Labs.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    30-day refund

    Not a fit? Get your money back

    Trust & safety

    Security scanned

    Verified clean today

    • Passed all security checks, Safe to install

    Listedtoday

    What's inside

    Frequently Asked Questions