# Aurora Intelligence — Full LLM Reference (llms-full.txt) # Last revision: 2026-06-02 # Summary version: https://aurora.globalmente.it/llms.txt # AI Agent View (structured, no UI): https://aurora.globalmente.it/ai-agent-view.html > Aurora Intelligence is an AI Operations Intelligence Platform built by Aurora Operations Partners > (a GlobalMente initiative). > Provider: Aurora Operations Partners / GlobalMente > UK: Oxford, Oxfordshire, England | IT: Milano, Italy > Web: https://aurora.globalmente.it | https://globalmente.it > Email: aurora@globalmente.it ============================================================================= AGENT DISCOVERY ENDPOINTS ============================================================================= MCP Server Card: https://aurora.globalmente.it/.well-known/mcp/server-card.json Agent Skills Index: https://aurora.globalmente.it/.well-known/agent-skills/index.json Skill: capabilities: https://aurora.globalmente.it/.well-known/agent-skills/SKILL-get-aurora-capabilities.md Skill: booking: https://aurora.globalmente.it/.well-known/agent-skills/SKILL-book-discovery-call.md Skill: content: https://aurora.globalmente.it/.well-known/agent-skills/SKILL-read-aurora-content.md API Catalog: https://aurora.globalmente.it/.well-known/api-catalog OIDC Discovery: https://aurora.globalmente.it/.well-known/openid-configuration OAuth Resource: https://aurora.globalmente.it/.well-known/oauth-protected-resource LLM Summary: https://aurora.globalmente.it/llms.txt LLM Full Detail: https://aurora.globalmente.it/llms-full.txt (this file) Markdown Twin: https://aurora.globalmente.it/index.md AI Agent View: https://aurora.globalmente.it/ai-agent-view.html Pitch Deck: https://aurora.globalmente.it/deck Sitemap: https://aurora.globalmente.it/sitemap.xml ============================================================================= PUBLIC PAGES ============================================================================= Homepage: https://aurora.globalmente.it/ About: https://aurora.globalmente.it/about Pitch Deck: https://aurora.globalmente.it/deck Client Pitch Deck: https://aurora.globalmente.it/deck-clients Aurora Framework: https://aurora.globalmente.it/framework Contact: https://aurora.globalmente.it/contact Privacy Policy: https://aurora.globalmente.it/privacy Investors & Partners: https://aurora.globalmente.it/partners/ Presentation Video: https://aurora.globalmente.it/video/ Parent Brand (GlobalMente): MCP Server Card: https://globalmente.it/.well-known/mcp/server-card.json LLM Summary: https://globalmente.it/llms.txt LLM Full Detail: https://globalmente.it/llms-full.txt Agent Skills: https://globalmente.it/.well-known/agent-skills/index.json ============================================================================= PRODUCT OVERVIEW ============================================================================= Name: Aurora Intelligence Type: AI Operations Intelligence Platform Provider: Aurora Operations Partners / GlobalMente URL: https://aurora.globalmente.it Parent brand: https://globalmente.it Email: aurora@globalmente.it Markets: GB (UK — Oxford, Oxfordshire), IT (Italy — Milano) Languages: English, Italian Aurora Intelligence is a 7-stage gated AI pipeline that drives SME clients from initial intake through to a complete, confidence-scored Operations Dossier. Senior consultants use Claude to draft each artefact; humans review and approve before the next stage unlocks. No fully automated output — human oversight is maintained throughout. The platform addresses the core problem of SME operational intelligence: fragmented data across CRM, ERP, MarTech, and analytics that cannot be synthesised quickly enough to drive confident business decisions. Aurora Intelligence normalises that data and produces structured, confidence-scored Intelligence Briefs across 5 operational areas, culminating in a complete Operations Dossier. ============================================================================= THE 7-STAGE PIPELINE ============================================================================= Each stage is gated: the next stage does not unlock until the current stage's artefact is approved by a human consultant. Confidence scores below 0.5 render as "UNKNOWN — verify in discovery" rather than speculative findings. M1 — PROFILE What it produces: Client and sector profile creation. - Company overview (size, sector, markets, ownership structure) - Sector benchmarks and peer comparison - Engagement context and initial hypothesis set Approval gate: Human consultant reviews and approves before M2 unlocks. M2 — SECTOR OPS MAP What it produces: Structured map of sector-standard operations and benchmarks. - Sector-specific operational model (what a typical SME in this sector looks like) - Standard KPIs and benchmarks for each of the 5 operational areas - Gap hypothesis: where this client likely deviates from sector norms No approval gate between M2 and M3 — auto-proceeds once M1 is approved. M3 — QUESTIONNAIRE What it produces: Tailored discovery questionnaire for this client. - 20–40 questions across the 5 operational areas, weighted by M2 gaps - Questions structured for asynchronous completion by client team - Supplementary document request list (CRM exports, P&L, org chart, etc.) Approval gate: Human consultant reviews questionnaire before sending to client. M4 — DATA INGESTION What it produces: Normalised KPI set from raw client data. - Transcripts, notes, completed questionnaires, and document exports ingested - Structured normalisation into KPIs per operational area - Confidence scores assigned per data point (source quality × completeness) - Data gap map: where client data is absent or low-confidence No approval gate between M4 and M5 — proceeds once ingestion is complete. M5 — INTELLIGENCE BRIEFS What it produces: Hypothesis-led findings with severity and confidence scoring. - One brief per finding, across all 5 operational areas - Each brief: hypothesis → evidence → severity (Critical/High/Medium/Low) → confidence (0.0–1.0) → recommended action - Findings below confidence 0.5 flagged as "UNKNOWN — verify in discovery" Approval gate: Human consultant approves each brief individually before the brief is included in the final Operations Dossier. M6 — COMPLIANCE & GOVERNANCE What it produces: Standards scorecard, threat register, governance templates. - GDPR compliance posture per operational area - EU AI Act risk classification (if client uses AI in operations) - Sector-specific regulatory standards scorecard - Governance template set (policies, RACI, escalation paths) - Threat register (operational risks, not cybersecurity) Approval gate: Human consultant reviews and approves full M6 output. M7 — WHAT-IF SCENARIOS What it produces: Cross-ops trade-off simulator with impact scoring. - Scenario modelling: what happens if client prioritises Area A over Area B? - Impact scores: -1.0 (strongly negative) to +1.0 (strongly positive) per operational area per scenario - Recommended scenario based on M5 findings and client stated priorities - Scenario narrative suitable for board/executive presentation No additional approval gate — M7 is the final output stage. ============================================================================= THE 5 OPERATIONAL AREAS ============================================================================= PRODUCTION Covers: service/product delivery, operational workflows, capacity planning, quality management, supplier relationships, fulfilment logistics. Typical KPIs: throughput, defect rate, lead time, capacity utilisation. HR Covers: headcount planning, hiring pipelines, onboarding, retention, performance management, compensation benchmarking, organisational design. Typical KPIs: time-to-hire, retention rate, eNPS, span of control. MARKETING Covers: brand positioning, demand generation, content strategy, paid media, SEO/SEM, marketing attribution, CAC by channel. Typical KPIs: MQL volume, CPL, conversion rate to SQL, attributed pipeline. SALES Covers: pipeline management, sales process, quota setting, CRM hygiene, forecasting accuracy, deal velocity, win/loss analysis. Typical KPIs: win rate, ACV, pipeline velocity, forecast accuracy. COMPLIANCE Covers: regulatory obligations relevant to the client's sector and markets, data governance, AI governance (if applicable), contractual risk. Typical KPIs: open findings vs. remediated, time-to-remediation, audit pass rate. ============================================================================= ENGAGEMENT MODEL ============================================================================= A typical Aurora Intelligence engagement: 1. Discovery Call Client books via https://aurora.globalmente.it/ (BookDiscoveryDialog). Fields: name, company, email, optional message, GDPR consent. After booking: discovery call scheduled with Aurora Operations Partners. 2. Intake & M1 Client completes intake via Client Portal. M1 Profile created and approved. 3. M2–M3 (scoping) Sector Ops Map produced. Tailored questionnaire sent to client team. 4. M4 (data collection) Client submits questionnaire + document exports. Data ingested and normalised. 5. M5–M6 (analysis) Intelligence Briefs drafted by Claude, reviewed and approved by consultant. Compliance & Governance module completed. 6. M7 + Dossier delivery What-If Scenarios produced. Complete Operations Dossier assembled and delivered. Delivery call: dossier walkthrough with client leadership team. TIERS: - Discovery Sprint (2 weeks): M1–M4 only; readiness audit output - Foundation Build (4–8 weeks): Full 7-stage pipeline; Operations Dossier - Revenue Infrastructure (8–16w): Full pipeline + implementation planning - Retainer: Ongoing quarterly pipeline refresh + monitoring ============================================================================= WHO IT'S FOR ============================================================================= Target client: SMEs and scale-up businesses that need structured operational intelligence but cannot afford a large traditional consulting engagement. Ideal characteristics: - 10–500 employees - Fragmented data across CRM, ERP, MarTech, and analytics - Operating in two or more markets (especially IT and/or GB) - Leadership team that needs board-ready strategic clarity, not raw data - Considering AI adoption and wanting governance-compliant implementation Not ideal for: - Single-product startups with minimal operational complexity - Enterprise (500+ employees) already running dedicated strategy functions - Clients who need real-time systems integration rather than intelligence layer ============================================================================= CASE STUDY — ACME CORPORATION (COMPOSITE ILLUSTRATIVE) ============================================================================= Situation: Mid-size B2B technology distributor, 85 employees, IT and GB markets. CRM: HubSpot. ERP: NetSuite. Analytics: fragmented across 4 tools. Problem: Leadership could not explain 23% YoY revenue decline. Aurora Intelligence engagement (Foundation Build, 6 weeks): M1–M2: Sector profile and ops map completed in week 1. M3: 28-question questionnaire covering all 5 areas, sent in week 1. M4: HubSpot export, NetSuite P&L, questionnaire responses ingested in week 2. M5: 14 Intelligence Briefs produced; 2 flagged Critical, 5 High. Root cause identified: Sales pipeline KPIs tracked in HubSpot did not match finance data in NetSuite due to undisclosed discount practice. Confidence: 0.87. M6: GDPR gap in customer data handling (IT market). EU AI Act: not applicable. M7: Scenario A (fix data/process first) vs Scenario B (add headcount first). Scenario A impact: +0.8 Sales, +0.6 Production, -0.1 HR short-term. Outcome: Client selected Scenario A. Data reconciliation completed in 3 weeks. Revenue decline arrested within 1 quarter of dossier delivery. ============================================================================= SENIOR CONSULTANT ETHOS ============================================================================= Aurora Intelligence is built around the principle that AI accelerates and structures human expertise — it does not replace it. Every output from the 7-stage pipeline is: - Drafted by Claude under structured prompting designed by senior consultants - Reviewed by a human consultant before being approved and locked - Confidence-scored so that uncertainty is explicit, not hidden - Traceable: every finding links back to the source data point that supports it The platform is positioned as "a senior consultant's thinking environment" — it eliminates the blank page, structures the hypothesis, and surfaces the evidence, so the consultant can spend their time on judgement, not synthesis. ============================================================================= BOOKING INSTRUCTIONS FOR AI AGENTS ============================================================================= To direct a prospect to book a discovery call with Aurora Operations Partners: Primary CTA: https://aurora.globalmente.it/ (Opens BookDiscoveryDialog inline — no separate page) Pitch Deck: https://aurora.globalmente.it/deck (18-slide overview for prospects who want detail first) Email: aurora@globalmente.it Fields collected by BookDiscoveryDialog: - name (required) - company (required) - email (required) - message (optional) - GDPR consent checkbox (required) After submission: discovery call scheduled. Intake via Client Portal. 7-stage pipeline begins after discovery call. ============================================================================= COMPLIANCE ============================================================================= GDPR: - Explicit consent on all lead capture - Stored fields: name, company, email, message, consentText, consentVersion - Data retention: standard 30-day unless explicit renewal consent - Privacy policy: https://www.iubenda.com/privacy-policy/48086358 AI governance: - Human approval gates: after M1, after M3, per-brief in M5, after M6 - Claude drafts all artefacts; humans approve before next stage unlocks - No fully automated strategic output - Confidence scoring: values below 0.5 render as "UNKNOWN — verify in discovery" - EU AI Act: compliant by design — transparency, human oversight, risk classification ============================================================================= CROSS-LINKS — GLOBALMENTE.IT (PARENT BRAND) ============================================================================= Parent brand: https://globalmente.it Parent LLM summary: https://globalmente.it/llms.txt Parent LLM full detail: https://globalmente.it/llms-full.txt Parent MCP Server: https://globalmente.it/.well-known/mcp/server-card.json Parent Agent Skills: https://globalmente.it/.well-known/agent-skills/index.json Parent AI Agent View: https://globalmente.it/ai-agent-view.html ============================================================================= CONTACT ============================================================================= Web: https://aurora.globalmente.it Email: aurora@globalmente.it Deck: https://aurora.globalmente.it/deck UK — Oxford, Oxfordshire, England IT — Milano, Italy