Use AI across your fund and portfolio.
Deliberately.

There is no sector database for early-stage digital financial services businesses in Bangladesh or climate-smart agribusinesses in Kenya. Tracxn and CB Insights have partial coverage. The GIIN Annual Investor Survey gives you sector benchmarks but not a live pipeline. No deal pipeline tool is natively built for frontier markets. Your sourcing runs on relationship networks, conference conversations, and introductions. That produces good deals in some years and a completely opaque pipeline in others. Every new sector search starts from scratch, and most of that work falls to the partner.

Fund Thesis System Prompt: the foundation that makes every tool in the program thesis-aware. Includes a Responsible AI Thesis Lens question embedded at configuration. Sector Monitoring Blueprint: where funds have access to Tracxn, CB Insights, or similar platforms, the blueprint draws on these as inputs; where they do not, the workflow functions without them. The GIIN Annual Investor Survey is the default benchmark source for impact sector comparisons. Prior Deals Reference Prompt: for funds on Fund II or later, a structured way to query your own previous IC memos and investment theses against a current opportunity, using your own portfolio history as the benchmark when public comps do not exist.

A good associate spends four hours on a CIM before the managing partner says no in three minutes. In frontier markets, the problem is worse: CIMs rarely follow standard formats, financials are mixed into narrative PDFs, and there is no Bloomberg equivalent to cross-check the numbers. Pitchbook covers some markets, but deal comp data for a Series A fintech in West Africa or an agritech in Bangladesh is thin at best. Meanwhile, confidential deal materials are moving into AI tools with no written data policy in place.

CIM Screening Workflow: a working n8n Starter Template available at launch. Structured extraction output including an AI/Data Risk Flag for portfolio companies using AI in customer-facing processes. Data Classification Brief covering what data can go where and at what tier.

A deal-killer found after $150,000 in legal fees was avoidable. That question had an answer three months earlier. Diligence in frontier markets has no standard playbook: regulatory filings may be incomplete, local advisors work on different timelines, and a market visit that would resolve a key question costs two days of travel. The five questions whose negative answer should stop the deal often go unasked until the legal engagement is already running.

Diligence & Verification Toolkit: Five Kill-Shot Questions framework (the questions whose negative answer stops the deal, defined before legal engagement begins), Responsible AI Diligence Questions, gap analysis prompts, Three-Step Verification Protocol, and AI governance checklist. Local Advisor Call Protocol: a prep, capture, and synthesis workflow for expert and local advisor calls. In frontier markets, formal expert networks are thin. The most important diligence input often comes from a call with a local advisor, regulatory specialist, or sector expert. This protocol structures how to prepare for those calls, capture what matters, and surface contradictions between what advisors say and what the documents show.

IC memos look different deal to deal. When the managing partner approves a deal, the reasoning stays in their head. It is never written down in a way the team can learn from. Pattern recognition across a portfolio of twelve investments is impossible when each one is documented differently. For DFI-backed funds, the problem compounds: DFI co-investors conduct their own diligence on your process, not just your returns. IC narratives need an impact section that holds up to that scrutiny. Generic ESG sections will not.

IC Memo Template with a Responsible AI IC Section standard in every memo, Term Sheet Benchmarking Prompt for pre-negotiation intelligence, and Decision Record Protocol: a record of every approval decision that builds into the fund's institutional memory over time.

You are on the board of seven companies across four time zones. Management accounts land 48 hours before the meeting. Your DFI co-investors expect evidence of active board engagement, not just board minutes. You show up having read everything and thought about nothing, because there was no time to think. The partner's job at the board table is to ask the questions nobody else will. That requires preparation that goes beyond reading the pack.

Board Briefing Workflow: a working n8n Starter Template available at launch. Four-step process: performance extraction, open action item tracking, strategic question generation, and partner authentication. Includes Responsible AI Board Questions for portfolio companies using AI in customer-facing processes. 100-Day Plan Framework Template.

Stress signals in frontier market portfolio companies surface later than they should. Currency moves, regulatory changes, and mobile money disruptions can reshape a company's business model in a single quarter. By the time the quarterly KPI report flags it, you are three months behind. Impact reporting for DFI-backed funds adds its own burden: IRIS+ metrics, SDG mapping, and cross-walks for FMO, IFC, BII, and AfDB each require a different format. The data already exists. Assembling it takes three days of partner time every quarter. And when a company is approaching exit readiness, the preparation should start 18 to 24 months before. Mapping potential acquirers, building the comparable transaction file, and drafting the impact narrative for acquirer diligence all require structured research that most funds start too late and do entirely manually.

Portfolio Monitoring Exception Report (monthly, 20-minute review), Impact Measurement Mapping Prompt (IRIS+ to SDG to DFI framework cross-walk for FMO, BII, IFC, OeEB, and AfDB), LP Narrative Drafting Workflow, Responsible AI Monitoring Addendum: five signals added to monthly monitoring: customer protection, exclusion risk, bias risk, model governance, and impact integrity. Exit Readiness Framework: acquirer mapping across regional strategics, DFI secondaries, and co-investor buyouts; comparable transaction analysis using Pitchbook where available and structured web research where not; and a draft exit impact narrative for acquirer diligence.

Capital raising from DFIs and impact LPs is 30 to 40 percent of partner time, with almost no AI in the workflow. DFIs and impact LPs want evidence of a real impact management process, not just a policy document. The case is built across every meeting, every deal, every quarter. The most valuable thing the fund builds over time (the intelligence from hundreds of management meetings, market visits, and sector conversations) sits in individual inboxes that nobody goes back to. When a new team member joins, a partner walks them through it. There is no system.

Meeting Intelligence Protocol (the USV model: every fund meeting transcribed, tagged, and surfaced into a proprietary knowledge base that compounds deal by deal), LP Relationship Management Workflow (drawing on Preqin for DFI deployment history and LP positioning where available; structured public DFI reporting where not), Updated Fund Thesis System Prompt, Fund Responsible AI Position Statement (draft language for LP due diligence responses, board materials, and DFI reporting), and the full Fund AI OS Configuration Summary: nine components assembled across seven sessions.