WWF
Educational Chatbot for Indigenous Communities
“The chatbot made complex carbon credit concepts accessible to communities who had never engaged with such programs before.”
Company
WWF (World Wildlife Fund) is one of the world's largest conservation organizations, working in nearly 100 countries to protect wildlife and wild places. They partner with indigenous communities on environmental programs including carbon credit initiatives.
Visit WWFIndustry
NGO / Environmental
Size
Global NGO
Location
Global
Carbon credit programs could transform indigenous communities, but the concepts were trapped in technical jargon and PDFs nobody reads. WWF needed to meet people where they are—on WhatsApp, in their language, without assuming any prior knowledge.
Traditional education methods failed because they assumed a baseline understanding that didn't exist. Community members needed patient, conversational guidance that could adapt to their questions and explain concepts multiple ways until they clicked.
“The chatbot made complex carbon credit concepts accessible to communities who had never engaged with such programs before.”
Program Director
WWF Environmental Programs
Knowledge gap blocking participation
- •
Language barriers: Technical documentation only available in English and formal Portuguese, not the local languages communities actually speak.
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Literacy assumptions: PDF guides assumed reading fluency that many community members don't have, making self-education impossible.
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Limited field resources: Not enough human educators to personally guide each community through the complex concepts of carbon credits and environmental economics.
“Community members wanted to participate in carbon credit programs, but they couldn't understand what they were signing up for. That's not informed consent.”
Accessible AI Education
We designed an AI education agent that lives where the community lives: on WhatsApp. The agent detects the user's language and adapts its explanations to be culturally relevant and easy to understand.
Instead of dumping information, the AI checks for understanding at every step. If a user seems confused, it rephrases the concept using simpler analogies. If a question is too complex, it seamlessly escalates to a human educator, ensuring trust is maintained.
Natural Language Interface
Users interact via WhatsApp using their native language and colloquial terms.
Natural Language Interface
Users interact via WhatsApp using their native language and colloquial terms.
Core Agent Logic
Inputs
Outputs
Adaptive Explanations
AI adapts explanation complexity based on user understanding.
Adaptive Explanations
AI adapts explanation complexity based on user understanding.
Core Agent Logic
Inputs
Outputs
Human Escalation
Complex questions escalate to human educators when needed.
Human Escalation
Complex questions escalate to human educators when needed.
Core Agent Logic
Inputs
Outputs
Bridging the Knowledge Gap
1000+
Community Members
Educated on carbon credits
90%
Comprehension Rate
Post-interaction surveys
3x
Program Enrollment
Increase in participation
“For the first time, our communities can access information about environmental programs in a way that feels natural and respectful.”
Community Liaison
WWF Field Team
Tech Stack
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