Case study • Agriculture• Field Sales
Real-Time Sales Intelligence Transforms Field-Based Operations in Agri-Sales
Our client, an early-stage startup focused on digitizing rural sales, built an AI-powered mobile app called Scribe to support field agents working with low-digital-literacy customers. The app allows voice-based data capture, transcription, and AI-driven coordination — empowering on-ground sales reps in the agriculture sector to take, track, and manage customer orders with real-time visibility and precision.
Success Highlights
Key Details
Industry: Software / AgriTech / Field Sales Care Geography: Rural USA
Platform: AI-powered mobile platform
Business Challenge
Field sales in rural sectors required a more intuitive, reliable, and efficient system to manage customer requirements and order flow.
Disconnected tools and manual order structuring caused misalignment between field teams and backend operations.
Our Solution Approach
We engineered a scalable, AI-powered backend infrastructure that enabled real-time transcription, domain-specific AI understanding, and fully automated order workflows — bridging the gap between sales agents in the field and fulfillment teams at the back office.
1 · Analyze
Field Challenges & User Context
We worked with the client to understand rural sales workflows and end-user constraints, identifying a clear need for voice-first interactions suited to low-connectivity, non-digital environments.
2 · Architect
Scalable Real-Time Backend
We designed a scalable backend using C# and .NET, with RavenDB and Redis to support real-time voice data processing and smooth data flow from field agents to backend systems.
3 · Activate
Transcription & Order Automation
We integrated real-time audio transcription using OpenAI’s Streaming API and trained domain-specific AI models. RAG enabled contextual follow-ups and automated conversion of conversations into structured orders.
4 · Integrate
Seamless Frontend Integration
The backend was seamlessly integrated with Flutter-based mobile and web applications, enabling automated order flow to fulfillment and reducing manual effort and visit time.
Technical Highlights
Backend built with C# and .NET CLR
Real-time caching with Redis Document database powered by RavenDB
Live audio transcription via OpenAI Streaming API
Retrieval-Augmented Generation (RAG) for contextual AI responses
Domain-specific AI vocabulary models
Seamless Flutter app integration
function processVoiceNote(voiceInput):
transcript = streamTranscription(voiceInput)
structuredData = parseTranscript(transcript, domain=”AgriSales”)
if isOrderRequest(structuredData):
order = generateOrderList(structuredData)
saveToBackend(order)
notifyWarehouse(order)
else:
logConversation(transcript)
Business Outcomes
The platform dramatically improved the quality, speed, and reliability of field-based sales in rural markets — setting a strong foundation for future growth.
70%
Reduction in Order Errors
Real-time transcription and AI-driven parsing minimized misunderstandings and ensured accurate order capturing.
2×
Faster Order Fulfillment
By automating backend workflows and streamlining coordination with the warehouse, fulfillment cycles were cut in half.
40%
Decrease in Sales Visit Time
Sales reps no longer relied on manual note-taking, allowing for quicker visits and more productive customer conversations.
Automated workflows reduced miscommunication between field and warehouse teams.
Voice-first design enabled ease-of-use in rural, offline areas.
Ready to Power Real-Time Intelligence for Your Field Teams?
Let’s build intelligent systems that connect frontline agents with backend operations — in real time, at scale, and with complete reliability.