AI-Driven Transcript Management System

When a forward-thinking startup approached us with a bold idea—to build an AI-first SaaS platform that helps users manage, search, and interact with call and meeting transcripts—we knew this project was right up our alley. With a tight deadline, a laser focus on speed, and a lean MVP mindset, the client was looking for a partner who could think pragmatically, move fast, and still deliver a technically solid foundation for future growth.

At E2logy, we’ve built a reputation for turning vision into value through purposeful technology. In this project, our goal was simple: transform a complex, multi-layered problem into a clean, intuitive solution. This article shares how we approached the project, the decisions we made, and the functional value we delivered through AI-powered, scalable, and smart solutions.

Understanding the Client’s Needs

The client envisioned a simple yet intelligent platform to help users:

• Automatically ingest transcripts from third-party APIs like Otter.ai, Zoom, and Fireflies.

• Organize transcripts into user-defined project folders.

• Summarize key insights.

• Build a searchable knowledge base with chat-based Q&A.

In essence, the goal was to create a helpful project companion—one that remembers what was discussed in meetings and makes that information easily accessible through a conversational interface.

The challenge? They needed a minimum viable product quickly. That meant avoiding unnecessary complexity—no custom infrastructure, no overbuilt features. Just efficient use of low-code tools, prebuilt templates, and proven frameworks to deliver something functional, scalable, and ready to test in the real world.

Our Approach

To meet the timeline and technical goals, we took a lean, agile approach from the start. We worked closely with the client to define the essential features and prioritize functionality that would bring clear value to users. Here’s how we approached the build:

Account Creation and Authentication

We began by setting up secure user authentication. We chose Firebase Auth for its speed and flexibility, supporting both OAuth (for services like Google) and standard email/password sign-ups.

This gave users a seamless onboarding experience while ensuring secure access to sensitive meeting transcripts—a critical requirement for any SaaS product handling private data.

Transcript Integration with Third-Party APIs

The next step focused on transcript ingestion.

We built API integrations with transcription services like Otter.ai, Fireflies, and Zoom. The platform allowed users to:

• Connect their transcription accounts

• Automatically pull in new transcripts

• Manually upload files when needed

We also implemented webhook-based triggers to keep content in sync in near real-time.

Parsing, Summarizing, and Organizing Content

Once transcripts were ingested, we converted the raw data into structured, usable formats. Using natural language processing, we:

• Split the transcripts into manageable segments

• Created short summaries

• Extracted useful metadata (e.g., speaker info, timestamps, and keywords)

Transcripts were sorted into user-defined projects with tagging functionality, making it easier to manage conversations across clients, teams, or topics—without the need for manual sorting.

Vector Storage for Fast, Semantic Search

To help users query their data naturally, we transformed transcript chunks into vector embeddings using OpenAI’s models. These were stored in a fast, scalable vector database.

This enabled semantic search and contextual Q&A—so users could ask questions like “What were the key points from the marketing sync?” and get meaningful responses drawn from their actual meeting content.

Chat-Based Q&A: Turning Transcripts into Conversations

Using OpenAI’s GPT-4 API, we added chat functionality to each project. This allowed users to:

• Ask questions about specific meetings

• Receive AI-generated responses based on their transcripts and summaries

• Find past insights without scanning through full-length documents

The result was a more conversational way to interact with project information—more intuitive than traditional search.

Deployment on Stable, Scalable Infrastructure

We deployed the platform to ensure performance, scalability, and low maintenance. The chosen stack supported:

• Serverless deployment for efficient scaling

• Real-time updates  

• A reliable PostgreSQL database for structured data

For backend logic, we used Firebase Functions to accelerate development and make updates easier during MVP cycles.

Uploading External Documents

Beyond transcripts, the platform supported uploads of other relevant documents—like PDFs or slide decks. These were also processed into vector format and added to the project’s knowledge base.

This expanded the scope of searchable data, allowing users to reference both conversation history and supporting materials in a unified interface.

By combining thoughtful integrations, AI-powered functionality, and a scalable architecture, we delivered an MVP that was both lean and effective—ready for real-world testing and future expansion.

Results Achieved

By following a lean development approach and working with a proven tech stack, we delivered a functional MVP in just four weeks. The client was pleased to see:

• User Onboarding: Over 150+ users signed up during the beta rollout

• Transcript Imports: More than 500 transcripts processed via integrations and manual uploads

• Response Accuracy: Chat-based Q&A returned over 85% relevant responses in user testing

• Performance: Average response time for semantic search and chat answers stayed under 1.2 seconds

• Platform Uptime: Maintained 99.9% uptime

• Development Efficiency: Reduced backend dev time by 30–40% using Firebase Functions and prebuilt components

Why Clients Trust E2logy for Fast-Moving MVPs

We at E2logy, don’t just deliver software—we focus on building the right product for where your business is today, while setting it up for tomorrow’s needs.

From working with third-party APIs and setting up AI-powered workflows to choosing infrastructure that supports long-term scalability, our team brings hands-on experience and a practical mindset to every build.

Looking to build something similar?

Whether you’re planning a lightweight MVP or a more robust AI-enabled solution, our team can help you move quickly without cutting corners. Reach out to us about how we can bring your product idea to life—just like we did with this transcript management platform.