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Global Nodes · B2B enterprise AI transformation for high-compliance industries

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Agenda

Today’s discussion

    Who we are

    An AI engineering partner for regulated enterprises

    We architect, build and run practical AI systems inside the enterprise. We leverage the tools, data and workflows a business already depends on.

    “GN are the rare partner who takes AI from whiteboard to operations without losing the thread. Deep engineering, clear communication, zero drama.”

    Craig A. Cook · Founder & CEO, Mobilads
    Simon MainwaringPartnerBestselling author, corporate strategist. Formerly Nike, Adidas
    Jacobo LumbrerasPartner5x founder, Forbes 30 Under 30. Formerly Upwork, PicPay
    Vikas GoyalPartnerFormerly Amazon, Emids, Daffodil
    Arvind AwasthiCTOFormerly Daffodil, BlackBerry
    Varsha SinghHead of DesignFormerly Dalmia, Quovantis, Emids
    Remo SahaHead of Marketing & MediaFormerly Digitally Global, Calance
    Clients and partnersClients include Brex, Amazon, Upwork, PicPay, NBCUniversal, Corelight, Neeka and others
    Four delivery hubs located to provide 24/7 serviceMiamiSão PauloMadridDelhi
    The state of AI · 2026

    Most AI programs stall before production

    $4.4T in annual value is on the table, and 70% of initiatives stall before scale. MCKINSEY GLOBAL INSTITUTE · 2026

    Where the money is going

    The money has moved to making AI actually do the work

    TodayWhat AI can doModels that read, write, reason and act
    $14B+invested in firms that make AI do real work
    The gap
    Connect your systemsPrepare your dataBuild in approvalsTrain your people
    TomorrowWork actually doneIn production, inside the business
    Who takes the money · 1

    Firms that close the gap for you

    They put AI to work inside your company: lab-backed deployment teams, independent implementers, platforms.

    This is where Global Nodes works.

    Who takes the money · 2

    Firms that close it for themselves

    They do the work themselves with AI: AI-native law firms, security and contact centres, roll-ups of accounting firms.

    What it means for you

    You will be pitched by both

    Ask every vendor for systems running in production, not demos. The mid-market is underserved, so the best partners are still available.

    SaaS was about enabling work functions. AI-native services are about delivering the actual work.

    What AI transformation actually is

    Most of AI transformation has little to do with AI

    The model is the part everyone sees. The outcome depends on the work underneath it.

    Approach

    Systems that stay up on Tuesday.

    An agent, in production

    One work order: 38 seconds and one approval

    From: dispatch@ridgeway-facilities.com08:14

    Urgent: HVAC unit failing at Store 214

    Hi team, Store 214 (Columbus, OH) reports rooftop unit 3 blowing warm air since this morning. Store opens at 9. Please raise against PO 88213, quoted at $5,150. Priority 1, customer-facing area.

    Thanks, Dana

    Illustrative workflow
    Agent trace · work-order agent00.0 s

    Approval needed. PO 88213 covers $4,200; the quote is $5,150. The unit is under warranty to 2027, so labour is $0. Proposed: send the warranty vendor and cap the PO at $1,180 for parts.

    38 sagent time
    47 minmanual baseline
    $3,970overspend avoided
    How development teams are changing

    Smaller teams, more leverage

    10 peopleteams reaching €50M in revenue within 18 months

    Becoming AI-native requires reinventing almost every role

    01Write your judgment downAGENTS.md, design.md, SOPs 02Make “good” checkableEvals, tests, holdouts 03Know where the agent stopsApprovals, exceptions
    Where we vibe-code, and where we engineer

    Prototyping with AI, engineering for production

    PrototypeGateProduction
    ⏱ hours, not weeks
    ›Prototype a claims triage dashboard
    Stage 1 · AI-assisted prototype

    Clickable prototypes, UI explorations and feasibility spikes, built in hours on sample data.

    e.g. a demo for Friday’s board meeting

    • Touches real customer or employee data
    • Someone will rely on its output
    • Writes to a system of record
    • Falls in regulatory scope
    Any one true → rebuild for production
    Stage 2 · the gate

    A prototype is never promoted. If it crosses the gate it becomes the specification, and the build starts clean.

    e.g. “Can a model read our warranty claims?”

    pipeline · mainProduction
    1. Threat model reviewed
    2. Engineer review · every AI-assisted change
    3. Unit and integration tests passed
    4. Evaluation suite above threshold
    5. Build signed and reproducible
    6. Deployed · audit log written
    Stage 3 · production engineering

    Built to be owned, audited and run by your team, with every gate enforced in CI.

    e.g. fraud scoring on live payments

    Tools in daily use
    Claude CodeRefactors, tests, migrationsCursorAI-native editorGitHub CopilotInline suggestionsFigma AIDesign to codeAntigravityRapid prototypes
    Agent harnesses

    The model is rented. The harness is yours.

    Modelthe reasoning engine · rented, swappable+Harnessloop, tools, memory, rules · built on your systems=Agentsworkers that do a job end to end, alone or as a team
    Closed modelsGPT · Claude · GeminiOpen-weight modelsLlama · Mistral · Qwen · DeepSeek
    What to turn into an agent

    Five tests decide: agent, automation or human

    Tests 1 to 4 ask whether a task can be automated at all. Test 5, judgment in the middle, decides whether it needs an agent.

    Pick an example
    Where agents fit in your business

    Not everything should be an agent

    Command center

    Seven AI platforms built by Global Nodes

    Each platform serves one executive function and includes a copilot that answers questions from its data.

    Products we built and launched

    From whiteboard to launch

    Case studies

    Results from systems in production

    Security

    Secure AI across seven layers

    Security decides who can reach your AI, and what it is allowed to do once they do.

    Why it matters now · agentic AI turns prompt injection into action injection
    #1Prompt injection in the OWASP Top 10 for LLM applications
    97%of organisations with an AI-related breach lacked proper AI access controls
    1 in 5reported a breach caused by shadow AI, adding about $670K to its cost
    2xrise in high-risk enterprise AI prompts in a year, from 1 in 50 to 1 in 25
    HIPAAIn production
    PCI DSSIn production
    SOC 2 Type IIIn audit
    ISO 27001Roadmap

    “In regulated AI, even an error message is a regulated change.”Lesson from RecoveryAI, built for the FDA De Novo pathway under HIPAA and SOC 2

    Data sovereignty

    Choose the sovereignty level per data class

    Sovereignty decides whose laws, servers and suppliers your AI depends on. We set it by jurisdiction, residency, cost and access risk.

    34%of enterprise AI tokens now run on open-weight models, up from 23%
    3.3%performance gap between leading closed and open models
    6–60xcost difference between open and closed models

    Hybrid routing Sensitive requests go to local models, everything else to frontier APIs, decided per data class.

      Why build instead of license
      “The value of IP no longer exists in software.”Chamath Palihapitiya, All-In Podcast, 2026
      1. 01

        Products can be rebuilt

        Photoshop, Premiere and Lightroom have already been rebuilt as free, open-source tools using AI.

        Photo editorVideo editorPhoto libraryopen sourcePetaPixel · Oct 2026 ↗Someone rebuilt free, open-source versions of Photoshop, Premiere and Lightroom using AI
      2. 02

        Services are going headless

        Agents call vendor APIs directly. The screen you license matters less every year.

        Salesforce blog · 2026 ↗Why Salesforce shifted to headless IT operations (and ditched the browser)
      3. 03

        Build what solves your problem

        Your process, data and judgment, encoded in software you own.

      ▶Watch the clipAll-In Podcast on X
      All-In Podcast · the clip behind the quote
      IP ownership

      You own what we (and you) build

      All source code, models, designs and documentation are owned by the enterprise. Fewer licence fees and locked-in vertical solutions; more tools you own. The only constant is continuous innovation.

      1. Run it yourselves, or with anyoneYour team or another vendor can take over. Nothing to buy back.
      2. Change models as the market movesThe layer around the model is yours, so switching provider is engineering work, not a contract.
      3. Answer auditors directlyYou hold the code, prompts and logs that explain how every decision was made.
      Owned by the company
      • Source codeIn repositories under your organisation
      • Prompts and agent definitionsThe logic that governs AI behaviour
      • Evaluation suitesTest sets and pass thresholds
      • Fine-tuned weightsAdapters and the training data behind them
      • Pipelines and infrastructureAs code, in your cloud account
      • Designs and runbooksArchitecture, operations and handover
      Remains under third-party licence
      Foundation modelsLicensed by the provider to youOpen-source componentsUnder their own licences
      How we staff itElastic contributors, not staff augmentation

      A small pod sized to each phase, from a tech lead to forward deployed engineers who embed with your team. Priced by role and outcome rather than headcount, scaled up or down between phases, and every line of code, IP and know-how handed over at the end.

      The limit on software used to be engineering.
      Now it’s mostly imagination.

      Greg Isenberg

      Thank you.

      3 Takeaways
      01 · What’s going onThe shift is funded and moving$14B+ is chasing AI’s last mile, and only 25% of enterprises have scaled AI beyond pilots.
      02 · How we prove itWe are already shipping it50+ AI transformation working platforms, launched products and systems in production within regulated industries.
      03 · Why it can’t waitThe window is short60% of that capital was committed in one quarter. EU high-risk AI duties apply from December 2027; India’s DPDP Act from May 2027. Policy is moving and so is competition.
      1. 01 · Week 1–2AI stack scanEvery tool and process screened, the 3 highest-value builds sized and scoped.
      2. 02 · Week 3–8Your data, your platformOne platform on your data, inside your perimeter.
      3. 03 · Week 9+ProductionHardened, governed and owned by your team.
      0hands raised for a 30-day pilot
      Follow up to learn moreScan or email us to get the interactive deck, PDF or a 30-min slot about your first deployment or use case.globalnodes.com · Miami · São Paulo · Madrid · Delhi
      Q&A

      Questions and discussion

      Describe an industry, a business problem or a concern. Responses draw only on work we have delivered and on how we operate.

      Suggested questions
      Ask Global Nodes
      Global Nodes
      Ask about an industry, a problem you want solved, or how we handle security, data, pricing and ownership.
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