x.1 Foundation × First Aviation Academy
Enter the access code provided by x.1 Foundation.
First Aviation Academy · Subic Bay, Philippines
A structured approach to six years of prospect data
x.1 Foundation · Pro Bono
Demonstrate that AI-powered data mining can transform 6 years of scattered, unstructured data into a complete, actionable sales intelligence system — with immediate, tangible value for FAA.
A fully populated historical dashboard with pipeline analytics, prospect insights, communication patterns, and a live HubSpot demo — built from FAA’s own real data.
A pro bono workshop under the x.1 Foundation mandate to empower Philippine organisations. FAA provides the data and infrastructure; x.1 provides the expertise and labour.
Since operations began, FAA has accumulated a rich history of prospect interactions. The problem isn’t a lack of data — it’s that the data is scattered across incompatible formats and systems.
Thousands of prospect emails across multiple mailboxes. Inquiries, follow-ups, negotiations, rejections — all untagged, unsorted, impossible to search by stage or outcome.
Outlook / ExchangeMultiple spreadsheets maintained by different staff members with varying column names, formats, and levels of completeness. Some have 200 rows, some 2,000.
Multiple Files / AuthorsMicrosoft Forms / website contact forms with structured data (name, email, program interest, country) — the most consistent source, but disconnected from follow-up records.
Microsoft Forms / WebsiteNotes from school visits, career fairs, and walk-in inquiries. Valuable leads captured on paper but never digitized or connected to digital records.
Paper / NotebooksFacebook Messenger is a primary inquiry channel in the Philippines. Conversations happen in DMs but are never captured in any database.
Messenger / InstagramPhone inquiries and walk-in visits captured informally — sometimes in a logbook, sometimes in a colleague’s memory. Critical context lost over time.
Informal RecordsEach of these becomes possible once the scattered data is unified, structured, and analysed with AI.
Discover response time patterns, follow-up cadence, peak inquiry seasons, and communication gaps. Learn how FAA talks to prospects and where the process breaks down.
Scope note: Email and webform data are accessible via API. Facebook Messenger and WhatsApp communications require separate access arrangements and are subject to further discussion — they may not be part of the initial workshop scope.
Identify recurring prospect profiles: the serious career changer, the price-sensitive parent, the foreign agent pipeline, the walk-in dreamer. Understand who enquires, through which channel, and why.
Note: PTC’s team has already developed prospect personas in a previous session. This layer will analyse the actual historical data and compare those findings against the existing personas — validating, refining, or replacing them based on evidence.
Connect email addresses and names across webforms, emails, spreadsheets, and enrollment records. Map a prospect’s complete journey from first inquiry to certification (or drop-off).
Build historical pipeline views with conversion rates, stage durations, bottleneck analysis, and trend lines. For the first time, a consolidated view of the complete historical funnel.
Understand why and when prospects disappear. Identify the stages with highest drop-off, the common last-touch patterns, and whether leads are truly lost or just forgotten.
Import the cleaned, structured data into a dedicated parallel HubSpot instance. A hands-on environment experiencing exactly what a production CRM looks like when populated with your own real historical data.
Extract best practices from successful enrollments. Which email templates worked? Which follow-up timing converted? What language resonated? Build a playbook from your own history.
A three-layer approach: Extract → Structure → Analyse
Infrastructure decision pending: The workshop system can run on either an Azure VM (if FAA already has an Azure environment) or a Linux VPS (lower cost, no existing cloud account required). This will be confirmed during the IT preparation call based on FAA’s current setup and preferences.
Every deliverable below is built during the 5-day workshop and handed over to FAA in full — including all code, data, and documentation. No ongoing dependency on x.1 Foundation.
All 6 years of prospect data — from every source — unified in a single, queryable SQL database. Every prospect matched across email, webform, and spreadsheet by email address and name.
Full historical pipeline with conversion rates per stage, time-in-stage distributions, seasonal patterns, lead source effectiveness, and year-over-year comparisons.
AI-generated persona profiles based on actual communication patterns: who enquires, through which channel, what they ask, and how long they take to decide. Compared against PTC’s existing persona model to validate, adapt, or refine it.
A detailed analysis of where and why prospects drop off — stage by stage. Last-touch patterns, common objections, and a clear picture of the 92 who didn’t make it for every 100 who enquired.
FAA’s real historical data loaded into a dedicated parallel HubSpot instance — showing exactly what the prospect pipeline, deal timeline, and contact records look like in a professional CRM. A working reference environment alongside the live HubSpot account.
The workshop builds the foundation. The following capabilities are not part of this workshop scope — but become natural next steps once the data infrastructure is in place.
Translating the data insights into a structured playbook: response templates, follow-up cadences, objection-handling scripts — derived from what FAA’s own history shows works. The workshop generates the raw findings; the playbook is the consulting step that turns them into operational procedures.
Merging the validated historical data from the workshop demo instance into FAA’s live HubSpot account — giving the active CRM a complete prospect history from day one. Requires careful data mapping, field alignment, and change management to avoid overwriting live records.
All email communications embedded in a searchable AI knowledge base. Ask questions like: “What did we discuss with Maria Santos about medical clearance?” and get instant, cited answers. Requires significant compute infrastructure and ongoing API costs — valuable, but not part of the initial workshop scope.
Applying the workshop models to new incoming inquiries in real time — scoring each prospect’s likelihood of enrolment based on profile, channel, and communication patterns identified in the historical data.
Extending the data scope to include Facebook Messenger, WhatsApp Business, and other inquiry channels currently not covered in the workshop. Each requires separate access arrangements, API setup, and data compliance review.
The workshop runs across approximately two to three weeks — mostly via online calls and remote collaboration, with concentrated hands-on sessions for the technical phases. Three milestone calls anchor the process: kickoff, midterm review, and final presentation. The pace adapts to team availability throughout.
An informal online session to present the proposal, walk through the IT preparation checklist together, and align on scope before any commitment is made.
Official start of the workshop. Everyone meets, roles are confirmed, and the timeline is locked.
x.1 Foundation and IT work together via screen-share to stand up the workshop environment and verify all data access is functional. All infrastructure decisions and access arrangements are documented and signed off.
Largely automated. x.1 runs the extraction pipeline; IT monitors and resolves any access issues. Brief daily async check-in (15 min call or message) to confirm progress.
AI resolves identities across sources and builds the unified database. IT, Sales, and Leadership all participate in reviewing outputs to confirm the data reflects operational reality.
A structured review of first findings before the final analysis phase begins. Leadership sees early results; the team aligns on any scope adjustments.
x.1 Foundation generates all final outputs. Sales is on-call for context questions. Deliverables are assembled and reviewed before the final presentation.
All five deliverables presented to the full team. Since IT has been a co-owner throughout, this session focuses on reviewing, validating, and agreeing on the outputs — not on a one-way handover.
x.1 Foundation provides the expertise and labour. FAA provides the data access and infrastructure. Every item below is formally documented and approved before work begins.
Executive sponsorship for the workshop. The CEO’s endorsement signals to both IT and Sales that this initiative has organisational backing and sets the tone for compliance with access requirements.
A server environment to run the data mining pipeline. All data stays within infrastructure controlled by FAA — nothing is processed on x.1 Foundation servers. Since FAA operates within the Microsoft Azure ecosystem, Azure VM is the recommended option:
An Anthropic API key registered under FAA’s own account, with sufficient budget to process thousands of emails and documents through AI classification and analysis.
Read-only OAuth access to the relevant mailboxes via Microsoft Graph API. For shared mailboxes (info@, sales@, admissions@), IT configures access. For individual salesperson mailboxes, written approval from each person is required before access is granted.
Mail.Read scope. x.1 team guides the full configuration. A formal access approval document will be prepared for each salesperson to sign.
Two HubSpot environments are needed for the workshop:
All available Excel files, Word documents, exported webform data, and any other records related to prospect tracking accumulated over the past 6 years.
IT has an intensive, active role throughout the entire workshop — not just in setup. The IT team handles infrastructure provisioning, API configuration, data access, validation sessions, and is a co-owner of the final outputs.
| Scenario | VM/mo | AI API/mo | Total/mo | Data Safety |
|---|---|---|---|---|
| A — Claude API | $180 | ~$10 | ~$200 | External (Anthropic) |
| B — OpenAI API | $180 | ~$5 | ~$205 | External (OpenAI) |
| C — Azure AI (Recommended) | $180 | ~$5 | ~$205 | Microsoft tenant |
| D — Own Model (Max Safety) | $720 | $0 | ~$740 | Zero external transfer |
| x.1 Foundation facilitation & engineering: Pro Bono (~120 hours) — FAA covers infrastructure only. | ||||
All scenarios include HubSpot Sandbox (free tier) and MS Graph API (included with M365). One-time cost: OpenAI Embeddings $0.50 (Scenarios A–C) or $0 (Scenario D). Pricing: Azure Southeast Asia, March 2026.
About the organisations delivering this workshop.
Philippine non-stock, non-profit corporation (SEC CN202003705) with a mandate to empower Filipino organisations and individuals through technology.
Role in this workshop: Strategy, AI engineering, data mining, analysis, and all deliverables — provided entirely pro bono.
A Hong Kong–registered executive communications consulting firm serving C-suite executives, keynote speakers, and their teams for over 30 years.
Four clear steps to move from proposal to workshop. Each step produces a signed document or confirmed decision before the next begins.
Share this proposal with the CEO and key decision makers — including the IT lead. We are happy to present a 15-minute executive briefing via Zoom or on-site at Subic Bay. IT must be present: they are a critical partner from day one, not a support function.
Formally approve the infrastructure choice (Linux VPS or Azure VM) and the following API accounts — each registered under FAA’s own accounts and documented:
x.1 Foundation prepares a documentation package for sign-off before work begins:
The workshop follows an Agile methodology: iterative, feedback-driven, and adaptive. All decisions and approvals are documented at each phase to ensure a fully auditable process.
Once approvals are in place, we schedule the Pre-Workshop Discovery Call with IT and Leadership, followed by the full Kickoff Call. IT begins infrastructure setup; the workshop begins. Results in approximately 10 working days.
This is the first step to introduce the supporting power of AI — how to empower people, not replace them.