Scaling Grassroot Leadership with Purpose Built AI
Summary
Impact Created
50%
increase in mentoring coverage
17%
reduction in per-fellow mentoring cost
30%
boost in buddy efficiency
About the organisation
I-Saksham is a grassroots nonprofit working to empower young women from marginalized communities as edu-leaders, equipping them to deliver quality education and transform their communities through a two-year fellowship program.
Problem Statement
I-Saksham faced significant bottlenecks in its peer coaching "Buddy Talk" process, essential for edu-leader development. Manual, time-intensive feedback led to delays (20-30 days), low buddy-to-fellow ratios (1:8), inconsistent coaching quality, and unstructured data, hindering efficient scaling of their human-centered mentoring model.
Solution
I-Saksham implemented an AI-assisted mentoring solution to streamline the "Buddy Talk" process. This involved leveraging technology to automate and accelerate feedback, reducing operational burden while maintaining a human-centered approach. The solution was rolled out using a phased, user-driven strategy, engaging field teams as co-designers to ensure effective adoption.
Key Learnings
- User-centric design is crucial for tech adoption and building trust.
- AI acts as a co-pilot, enhancing human work, not replacing it.
- Small, contextual innovations can drive significant systemic change.
Key technology Used
- Whisper (audio transcription)
- Gemini (LLM summarization)
- Custom MIS
- Google Workspace
- Azure
- AWS
- Zoom
- WhatsApp Chatbot
Quick Facts
Organisation Name
I-Saksham
Organisation Website
Visit Site
Founding Year
2015
Number of Beneficiaries served
600+ fellows trained, impacting over 12,000 children and 10,000 parents
Geography Served
Rural Bihar
Focus Area
Programmatic Impact, Operational Efficiency, Capacity Building
Functions Impacted
Program Delivery, Peer Coaching, Internal Feedback Systems
SDG Addressed
Full Case Study
Challenges
Peer coaching at I-Saksham hit a bottleneck due to unstructured support for buddies and a time-heavy feedback process that delayed insights and strained capacity.
Every edu leader is assigned a coach known as a buddy and the peer coaching conversations are key to the development of the edu leader. Building capacity of buddies to conduct effective coaching is also critical as they are recent graduates from the fellowship.
As the fellowship scaled, I-Saksham faced a key bottleneck in its Buddy Talk process—the peer coaching conversations between edu-leaders and their assigned buddies. Since buddies were recent graduates, they too needed structured support, creating a dual mentoring requirement.
The manual, two-step feedback process was time intensive. Buddies submitted detailed forms after each session, which were reviewed by mentors who added their own feedback. Each cycle took 30 to 60 minutes, placing a heavy documentation burden on both roles.
This led to delayed feedback (20–30 days), low buddy-to-fellow ratios (1:8), inconsistent coaching quality, and unstructured data that was difficult to analyze. i-Saksham needed a solution that would reduce this operational load without compromising its human-centered mentoring model.
Solution
Solution Development
This led to a roll out of a user-led tech solution that streamlined peer coaching by enhancing human processes through co-design and iterative pilots.
The solution rollout followed a phased, user-driven approach. Starting with pilot cohorts, the tech was tested, adapted, and integrated into existing workflows. Field teams were treated as co-designers, not end users fostering trust and ensuring adoption.
A lean, 7-member tech/data team supported implementation, and monthly review cycles maintained strategic alignment. The focus wasn’t on replacing human processes but making them faster, lighter, and more consistent.
Outcomes & Impact
Impact
AI-assisted mentoring enhanced efficiency, improved feedback quality, and enabled scalable, human-centered growth
The shift to AI-assisted mentoring produced outsized results:
- 50% increase in mentoring coverage (8 → 12–16 fellows per buddy)
- 17% reduction in per-fellow mentoring cost
- 30% boost in buddy efficiency
- Significant improvement in feedback quality and timeliness
- Staff time freed for coaching and strategic focus
- Program scaled without compromising its core values
- Not just digital transformation but human enablement at scale.
Tech Stack
| Tools / Vendors | Purpose |
|---|---|
| Google Workspace | Early MIS setup |
| Gemini 1.5 | AI-based transcription & feedback summarization |
| Azure & AWS Credits | Cloud infrastructure |
| Custom MIS + WhatsApp Bot | Reporting, integration, user adoption |
| Zoom | Remote mentoring and communication |
The result: a tightly integrated system that worked with users, not against them.
Adaptability In the Sector
- NGOs running mentoring or fellowship programs (e.g., TFI, Piramal Foundation)
- Healthcare nonprofits supervising field workers
- CSR programs tracking trainers or volunteers
- Rural incubators offering coaching/mentoring
- Any org using call-based support or peer feedback loops
