Case studies
Traq.ai
Case study

Traq.ai Accelerates Roadmap

How Traq transformed it from a parking lot into a race track with Lamatic.ai

Rapid delivery
AI capabilities ship far faster with managed infrastructure
Reduced code burden
Major portions of AI-related code retired instantly
Full product focus
Engineering attention freed from maintenance to innovation
Table of contents
Capabilities
ETL
Semantic Search
RAG
GraphQL API
Widgets
Serverless Edge
Use Case
Rapid GenAI Feature Deployment
Company
http://Traq.ai

Overview

Traq.ai, co-founded by Adam Rubenstein (CEO) and Pete Rice (CTO), is on a mission to help companies consistently win deals and accelerate time to revenue with their AI-powered conversation intelligence platform. The platform listens, analyzes, and delivers insights that enable sales organizations to achieve repeatable success by coaching sales teams and providing actionable recommendations. However, despite its powerful potential, the Traq.ai team encountered significant technical roadblocks on the way to realizing their full vision.

The Challenge:

Technical Debt and Slow Development

For Adam and Pete, speed was not just a business priority; it was the foundation of their competitive advantage. “At no point in history has speed been more central to success than it is today,” Adam noted. But developing and maintaining AI-driven sales solutions is complex and costly, particularly when engineering talent is scarce.

Adam identified three major challenges:

  • Scarce and expensive engineering talent: They needed experts to handle integrations and LLM engineering, which proved hard to find.  
  • Inability to iterate prompts with real data: The team struggled to improve AI performance because it was difficult to fine-tune prompts using production data.  
  • Difficulty deploying AI-based internal tools: Building these tools distracted from their core product development, slowing down overall progress.

Pete, on the technical side, faced additional hurdles:

  • Fragmented development environments: Passing prompts between different environments made testing and deployment cumbersome.  
  • Deployment inefficiencies: Releasing new updates across the platform was slow and tedious.  
  • Vectorization complexity: Traq.ai needed to vectorize conversations across people, organizations, and time periods to support both specific and summary Q&A capabilities, but this was technically challenging.

With these obstacles, the Traq.ai roadmap was stalling, and the growing technical debt was becoming a serious concern.

The Solution:

Partner with Lamatic.ai

Traq.ai found their answer in Lamatic.ai’s managed platform. For Pete, the decision to re-platform was clear. “ Speed and agility are all about focus. We don’t build and maintain things we don’t have to,” he explained. Lamatic’s platform provided an immediate solution to many of the challenges they were facing, instantly unlocking features that had been stuck on their roadmap for months.

Roadmap Accelerator⚡

Lamatic.ai enabled Traq.ai to deploy AI features and iterate prompts much faster by providing a streamlined, managed environment. Pete described it as a “roadmap accelerator”— new features that once seemed months away could now be delivered quickly and reliably. The platform also supported vectorization, enabling Traq.ai to offer both specific and summary Q&A insights across conversations, organizations, and timeframes.

By switching to Lamatic.ai, Traq.ai was able to retire thousands of lines of code, drastically reducing the burden of maintaining their AI infrastructure. “Deploying Lamatic instantly gave us 3 items that had been on our roadmap for months, Pete said. This not only improved the platform's performance but also freed up the engineering team to focus on the core product instead of getting bogged down by technical debt.

The Impact

  • Faster Time-to-Market: Traq.ai’s release cycles sped up significantly, allowing them to bring new AI features to market 5x faster.  
  • Reduced Technical Debt: Thousands of lines of code were eliminated, lightening the engineering load.  
  • Better AI Performance: With real-time data integration and prompt iteration, the quality of AI-driven insights improved.  
  • Focus on Core Product: Traq.ai’s engineering team could shift their focus back to driving core product innovation, without worrying about maintaining their complex AI infrastructure.

For Traq.ai, speed is everything. By partnering with Lamatic.ai, they were able to dramatically accelerate their product development, reduce technical debt, and focus on what matters most—delivering a world-class AI-powered conversation intelligence platform to their customers.

Smart, user-friendly, and incredibly valuable – Lamatic is the perfect solution.

Adam Rubenstein
CEO

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