AI-Powered Intelligence
Smart automation that learns from your network, powered by open-source AI
The challenge & our answer
The Problem
Finding the right partners, opportunities, and resources across thousands of organizations is overwhelming. Traditional search misses semantic connections, manual data entry is time-consuming, and quality control requires constant human oversight. Small organizations lack the institutional knowledge that large NGOs accumulate over decades.
The Solution
Action Network Worldwide uses AI to surface relevant connections you would otherwise miss, extract structured data from unstructured sources, and learn from successful collaborations to improve future suggestions. All algorithms are open-source and auditable — no black-box models, no vendor lock-in.
Key Capabilities
Semantic Matching
AI embeddings capture meaning beyond keywords. "Agroforestry" matches "regenerative agriculture" even when tags don't overlap exactly. Three-layer scoring combines deterministic set matching, semantic similarity, and geographic proximity.
Opportunity Extraction
AI reads funding alerts, partner requests, and web sources to extract structured opportunities automatically. Trust scores combine source reliability, extraction confidence, and completeness. Community corrections feed back into the extraction model.
Smart Autofill
Upload a project proposal or paste raw text — AI extracts structured fields with per-field confidence scores. Works for opportunities, workspaces, knowledge entries, and profiles. You review and approve, AI handles the tedious data entry.
Deliverable Suggestions
When creating a workspace, AI suggests deliverables based on the opportunity context or uploaded work plan. Learns from archived workspace patterns — the more workspaces complete, the better the suggestions become.
Content Classification
AI categorizes knowledge entries, assigns tags from the platform taxonomy, and generates summaries. Supports PDF, DOCX, and plain text uploads. All suggestions are advisory — human judgment always has the final word.
Quality Gates
AI flags low-relevance contributions, detects language mismatches, and surfaces potential issues for coordinator review. Advisory only — never auto-rejects. Quality emerges from data patterns, not manual rules.
How It Works
You provide context
Fill in your profile interests, upload a funding call, or paste a project description. The more context you provide, the better the AI understands your needs.
AI processes and suggests
Embeddings are generated, semantic similarity computed, and structured fields extracted. Trust scores and confidence levels accompany every AI output.
You review and approve
AI suggestions are pre-filled into forms with confidence badges. You adjust any fields, accept or reject suggestions. AI never auto-publishes or auto-decides.
System learns from feedback
Your decisions (accepted corrections, completed connections, archived workspaces) feed back into the matching engine and extraction models. The platform gets smarter with use.
Ready to get started?
Free to join — see plans & pricing →Frequently asked questions
Is my data used to train AI models?
No. Your profile and content are not sent to third-party model training. The platform runs open-source embedding models (nomic-embed-text) on its own infrastructure to power semantic matching. AI sees your data only to serve you better matches and suggestions.
Which AI models does the platform use?
All matching, classification, and extraction runs on open-source models — currently nomic-embed-text for embeddings and open small-LLM models for autofill and classification. No vendor lock-in. Models are auditable and swappable.
Can AI auto-publish or auto-decide anything?
No. AI is strictly advisory. Every AI output — extracted opportunity fields, classification suggestions, deliverable proposals — comes with a confidence score, and a human must review and approve before it takes effect.
How does the AI get smarter over time?
When you accept, correct, or reject AI suggestions, those decisions feed back into the matching engine and extraction models. Completed connections and archived workspaces become training signal. The platform learns from real outcomes, not synthetic data.
Can I opt out of AI-powered features?
AI is strictly advisory — it never auto-decides, and you can ignore any suggestion. Manual entry, manual search, and human-curated discovery are always available, so you can work without relying on AI at all.