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Case StudySoftware Development & Engineering
Global Software Company (500+ Developers)

Reducing Developer Onboarding from Weeks to Days with TruSynth

A global software company cut developer onboarding time from 3 weeks to 3 days using TruSynth's Software Intelligence platform—an agentic system that makes codebases self-explanatory.

5 min readSeptember 10, 2024
Primary Impact
3 Days
Developer Onboarding Time
3 weeks → 3 days
Onboarding Time
Time to first meaningful code contribution reduced by 85%
8 hrs/week recovered
Senior Engineer Time
Per senior engineer, time spent answering new-joiner questions eliminated
91%
Knowledge Retention
91% of new joiners passed a codebase knowledge assessment at 30 days vs. 54% previously
+62
Onboarding NPS
Net Promoter Score for onboarding experience, up from +11 before TruSynth deployment

The Challenge

The company's engineering teams struggled with a persistent onboarding problem: new developers required 3-4 weeks before becoming productive contributors to the codebase. The root cause was knowledge fragmentation—architecture decisions documented in outdated Confluence pages, institutional knowledge living only in senior engineers' heads, and a codebase of 2.4 million lines spread across 180 repositories with inconsistent documentation. Senior engineers spent an average of 8 hours per week answering repetitive questions from new joiners, creating a significant cost and distraction.

The Solution

Eficens deployed TruSynth, a Software Intelligence platform that creates a living knowledge layer over the codebase. TruSynth continuously indexes the codebase, documentation, Confluence, Jira, and Slack history to build a semantic understanding of the software system, then provides new developers with an AI assistant that can answer questions about architecture, explain code sections, trace the history of design decisions, and generate contextual onboarding guides.

Implementation

Codebase Indexing and Knowledge Graph Construction

TruSynth indexes the company's 180 repositories using a combination of static analysis and semantic embedding. Static analysis extracts structural relationships: function calls, module dependencies, class hierarchies, and configuration linkages. Semantic embedding captures the conceptual meaning of each code component, enabling queries like "how does the authentication system work?" to retrieve relevant code, documentation, and architectural discussions even when the query terminology doesn't match the code variable names.

Cross-Source Knowledge Integration

Beyond the codebase, TruSynth ingests the company's Confluence documentation space (450,000 pages), Jira project history (12 years of issues and comments), and a curated index of Slack architecture discussion channels. Knowledge graph edges connect code entities to the discussions and decisions that shaped them, enabling questions like "why was this database schema designed this way?" to retrieve not just the current schema but the original design discussion where the trade-offs were debated.

Personalized Onboarding Path Generation

For each new joiner, TruSynth generates a personalized onboarding path based on their role, assigned team, and first project. The path includes curated reading lists, guided code exploration exercises with AI explanations, and a schedule for "deep dive" sessions on the systems most relevant to their work. Progress is tracked in a dashboard visible to both the new joiner and their manager, with automated check-ins at days 3, 7, and 14 to identify gaps in understanding before they become productivity blockers.