CTO Compass
AI assistant to support engineering leaders in solving complex project challenges, providing actionable insights from our extensive knowledge base.Guided experience that allows for in depth analysis of your case with a knowledgeable AI assistant.
Key Outcome: Over 70% of recommendations are highly relevant, helping especially less experienced leaders quickly adopt best practices.
Quick Project Overview
Engineering leaders often confront a wide range of challenges - from process optimization and team coordination to architectural decisions and technical debt.
CTO Compass was born out of our desire to deliver:
- An AI assistant that goes beyond a generic chatbot by incorporating retrieval-augmented generation (RAG), specialized Large Language Model (LLM) roles, and framework-based templates (e.g., DORA, SAFe).
- Whole experience is support with the usage of Microtools, summarizing the outputs, providing them in procedural manner.
- Multimodal access for users - leaders can interact via text or voice, allowing flexible engagement and more natural conversations.
Key Achievements
High-Value Recommendations
Roughly 70% of suggestions directly map to real-world challenges, producing an average of 3–4 actionable insights per session.
Enhanced Multimodality
Users can type or speak their questions, making the system more accessible and conversational in real-time.
Adaptive Conversational Flow
CTO Compass dynamically adjusts its questions based on user input - shortening or extending the conversation depending on the problem’s complexity.
Microtools
Allowing users to explore each piece of insight separately, and asking in-depth questions within a specific insight's context.
The Challenge: Ensuring Relevance & Accuracy
A low-quality AI system is easy to build, but an AI assistant that delivers relevant and accurate insights is a greater challenge.
CTO Compass needed to:
- Contextualize recommendations for engineering leadership scenarios.
- Maintain alignment with proven frameworks (e.g., DORA, SAFe) and our knowledge base, ensuring the system’s advice is grounded in industry best practices and real-world experience.
Key Question: How can we ensure each suggestion is not only correct but also actionable and immediately beneficial to a product leader?
Our AI-Driven Approach
Maximizing Multimodal User Engagement
From day one, we adopted a user-centric design and frequent testing:
- Initial Text-Based Interactions: Early pilots used a fixed set of 10 questions, revealing a need for more natural, free-flowing conversation.
- Voice Interface Roll-Out: We introduced voice interactions to replicate the feel of talking with a real consultant, removing friction for users who prefer speaking over typing.
- Dynamic, Contextual Follow-Ups: Based on user input - whether text or voice - the AI assistant modifies its line of questioning, leading to deeper insights when needed or quicker conclusions for straightforward issues.
Example: A CTO discussing deployment bottlenecks can explain the scenario via voice, and CTO Compass will intelligently prompt for more details on CI/CD or automation before offering a set of next steps.
Results & Impact
Highly Relevant Recommendations
User feedback indicates that 70% of the system’s suggestions solve or significantly improve the stated issue. On average, each session provides 3–4 genuinely impactful insights.
Accelerated Learning Curve
Less experienced leaders find immediate value in tailored, best-practice-based advice, helping them implement improvements without needing an external consultant on standby.
Behavioral Insights & Analytics
An analytics module tracks user queries, identifies common pain points (e.g., team communication, performance bottlenecks), and offers data-driven direction for future enhancements.
Configurable Tuning & Rapid Iteration
With a flexible configuration setup, we can quickly adjust conversation flows, LLM prompts, and knowledge sources as user needs evolve - keeping CTO Compass current with new technologies and frameworks.
A New Paradigm for AI Consulting
CTO Compass underscores our expertise in AI solutions - combining agentic LLM systems, retrieval augmentation, framework-based guidance, and multimodal access (text + voice) to create an AI assistant that truly understands engineering leaders’ needs.