Assisted Support for Human-Led Conversations

An AI agent designed to scale real-time support without losing human touch

Client

Empower Work is a U.S.-based non-profit organization providing confidential, real-time chat support to individuals facing challenges at work. Their support model is built around trained human volunteers who deliver empathetic, one-on-one guidance in sensitive situations where trust, tone, and human judgment are critical.

“GreenM helped us turn an ambitious idea into a working AI-assisted workflow that truly supports our volunteers, while keeping the human connection at the core of our mission.”

Rajiv Puranik, CTO, Empower Work

7+ Years

Providing confidential workplace support

~500k

people supported across the United States

90%

of respondents report feeling better after a support session

Award Winning

“Five Standout Tech Nonprofits of 2022” by Forbes

What we did

GreenM designed and implemented an AI-assisted support workflow embedded directly into Empower Work’s existing live chat environment. The solution provides real-time guidance during conversations, helping volunteers respond with confidence and consistency.

Scalable support without compromising empathy

In 2024, demand for Empower Work’s text-based support doubled and continued to rise into 2025. As volume grew, operational constraints began to limit capacity, consistency, and volunteer confidence during real-time conversations. Scaling through traditional means would have required lowering quality or significantly increasing operational overhead — both incompatible with the organization’s mission.

How It Was

Capacity ceiling

Volunteers could manage ~2 simultaneous chats

Long, high-focus sessions

Average conversation length: ~50 minutes

Strict time pressure

Expected reply time: <3 minutes

“Stuck” moments in conversations

Uncertainty in responses reduced confidence

Manual workflows

Summaries, handoffs, and resource lookup were manual

Limited scalability

Growing demand translated into higher workload

The Solution

GreenM embedded contextual intelligence directly into live chat environment. During conversations, the system provides contextual, editable suggestions to support responses, while maintaining full human control and enabling fast access to relevant resources and internal knowledge.

Key Capabilities

Contextual, editable guidance in real time

Human-first response support

Fast access to internal knowledge

Privacy-aware processing

Seamless workflow integration

Outcomes

The AI-assisted workflow delivered measurable improvements across volunteer efficiency, support quality, and operational scalability.

“It’s like having an extra set of eyes watching the road, yet I am still driving.”

Cyn, Peer Counselor, Empower Work’

Increased capacity

Managing 3+ simultaneous conversations doubled (27% → 53%

Higher confidence and quality

93% rated the assistant as helpful, 70% as very to extremely helpful

Faster resource access

41% reduction in time spent sharing resources during conversations.

Reduced admin effort

Post-session summaries completed up to 60% faster.

Strong adoption

Actively used by ~65% of volunteers during live shifts.

Delivery

The solution was developed in close collaboration between GreenM and Empower Work to bring a production-ready AI-assisted workflow into live operations quickly, while enabling continuous improvement based on real usage.

Phase 1 
‍Human-Centered Workflow Design

Design of a human-in-the-loop AI workflow defining where AI assists and where human judgment remains final in sensitive, live conversations.

Phase 2  
Retrieval-Augmented Implementation

Embedded AI assistance built using retrieval-augmented generation (RAG) to surface relevant context from vetted internal resources and prior conversations, without model fine-tuning.

Phase 3 
‍Human-in-
the-Loop Production Release

Production-ready AI-assisted workflow deployed for real-time conversations, with all suggestions optional, editable, and fully controlled by volunteers.

Phase 4 
‍Feedback-Driven Continuous Improvement

Continuous refinement of prompts, retrieval logic, and user experience based on volunteer feedback and real production usage.

Security by Design

AI assistance was introduced in a way that preserves confidentiality, human oversight, and responsible use in sensitive, real-time support environments.