The Challenges
Join us on the Pragmatic AI Adoption journey if you face any of these challenges:
- Unclear Use Cases: Would you like to “do something with AI” but are not sure about the best use cases and how it truly helps your engineers and business goals?
- Bad Data: Is your data messy, siloed, or incomplete, making it hard to use for effective AI models?
- Skill Gaps: Do your team members have different levels of excitement, knowledge, and experience about AI tools?
- Security Risks: Are you worried about privacy, data leaks, or uncontrolled AI usage in your development work?
- Change Resistance: Do you struggle to balance new ideas with keeping things stable, making sure new AI features don’t break existing workflows?
Our Approach
We use a practical, engineering-first approach that aligns AI use with your real-world workflows and limits. Our journey has four focused steps:
- AI Strategy Workshop: We find clear goals and use cases where AI makes sense and check where it can help your engineering teams. We find AI solutions to real problems, not the other way around.
- AI Tool Adoption: Together, we use the findings from the AI Workshop. We carefully bring in the right AI agents and tools while keeping your engineers on board, set clear expectations, safe usage patterns, and training across all skill levels.
- Workflow Automation: Next, we look at the business processes within your teams. We find repetitive or manual tasks and design AI-driven workflows to automate them.
- Internal Data Connection: Now, we can connect your internal data sources safely to your AI models. This unlocks their true power as they have context about your company and can answer questions about it using Retrieval-Augmented Generation (RAG).
Your Results
| Result | The Value You Get |
|---|---|
| Clear AI Use Cases | A set of clearly defined use cases where AI makes sense to be used. We find AI solutions to real problems, not the other way around. |
| AI-Empowered Engineers | Engineering teams that use AI and automation with confidence while keeping control, quality, and security. |
| Smart Workflows | Repetitive, low-value tasks are automated, freeing engineers to focus on new ideas and customer impact. This is possible through the use of RAG and internal data sources. |
| Safe AI Usage | Clear guardrails and rules ensuring privacy, compliance, and ethical use of AI tools. |
