Case Studies
Real-world success stories of businesses we've helped transform through strategic AI implementation
Chatzy AI
Automated AI Agent Quality Monitoring System
LLM-as-a-Judge evaluation pipeline and two-tier monitoring architecture to surface failure modes, prioritize improvement areas, and close the loop between agent performance data and system optimization.
Key Results
- Automated evaluation replacing manual review of chat logs at scale
- Knowledge gap identified as the dominant failure mode across all clients
- Bot-type-specific failure patterns surfaced, informing a taxonomy-aware two-tier monitoring system
Riventra
Understanding and Modernizing Legacy Codebases
Intelligent and automated modernization of legacy codebases using LLMs, AST analysis, and GraphRAG. An MVP for Java systems that strips out dead code, surfaces the business logic buried inside, and adds new features on top.
Key Results
- Automated code cleanup on medium-sized Java repositories
- Unanimous expert approval for LLM-generated comprehensions and refactorings
- High success rate for new feature additions
ListenBravo
AI-Powered Account Research for B2B Sales
AI agents with web search and browsing capabilities to enrich lead databases on-demand, helping revenue teams discover accounts and find expansion opportunities.
Key Results
- Reduced MQL to SQL qualification time by 90%
- Increased sales pipeline by $10,000/quarter on average
- Reduced average SDR required per campaign from 10 to 3
Snapshots
Shorter looks at some of our other engagements
SmartMoney AI
AI for personal finance management
SmartMoney aims to develop an AI-native personalized financial guide especially for young Indians. With us, they brainstormed on the application of AI for consumer budgeting, financial modeling and investment advisory. While we emphasized the potential for AI to provide explainable investment insights and improve advisor productivity, we stressed on the importance of human-in-the-loop to manage trust and regulatory concerns.
Brew
Agentic-coding best practices
Brew came to us seeking advice on agentic-coding best practices before beginning to implement the backend for their already completed frontend. This included model choices, agent memory, rules and workflow (TDD, plan-execute-test loop, e2e integration etc.) best practices and relevant references. With a little care, their team was subsequently able to successfully implement the backend on their chosen tech stack in one month.
Zyod
Manufacturing efficiency using AI
In multiple strategy sessions, Zyod and Akrta analysed the opportunities AI can bring in improving fashion manufacturing efficiency in all stages from analyzing customer trends, forecasting demand for designs, inventory optimization through to AI-optimized production workflows. We also discussed the vast potential of rapidly improving computer vision capabilities in implementing automated quality control.
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