United KingdomTechnology and telecom2026 – ongoingEndava
Dava.Flow AI-native engagement lifecycle on Miro
Endava ran client discovery on Miro's AI workspace and reported cycle times up to 40% shorter in some engagements
Problem
Endava delivers software work for clients across many industries. Discovery, design and engineering handoffs ran in separate tools, so decisions and context were lost between stages.
Approach
Endava built Dava.Flow, an engagement lifecycle that pairs coding agents with Miro's AI Innovation Workspace. Teams run discovery and solution shaping with clients in shared visual boards. The boards generate personas, user journeys, prototypes, requirements and technical diagrams from research material. Templates and automation standardize technical reviews, risk checks and approval gates across hundreds of concurrent client engagements.
Results
Takeaway
Endava tied the visual workspace to the later engineering specifications, so engineers could see why a decision was made. The cycle-time figure comes from Miro and applies only to certain contexts.
Categories
- Size
- Large enterprise
- Industry
- Technology and telecom
- Business function
- IT and R&D
- Innovation type
- Process innovation
- AI technology
- Generative AIAI agents
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Miro's Chief Transformation Officer describes how Endava, with about 11,000 employees, uses Miro's AI workspace inside Dava.Flow for discovery, solution shaping and standardized reviews. It reports cycle time down by up to 40% in certain contexts. The figure is vendor-reported and the article gives no exact engagement count.
Full details are in the original sources.
