Yoti case study
AI & DataDigital Strategy

Yoti

AI Engineering Excellence Workshop

Full-day technical workshop driving 60% AI tool adoption in 30 days across Yoti's 200+ engineer organisation. Vendor-neutral evaluation, agent-led workflows, and governance for regulated identity verification.

60%
Engineering AI adoption in 30 days
90%
Target adoption by Phase 2
Phase 2
Follow-on engagement secured
200+
Engineers in organisation

The Challenge

Yoti, a leading digital identity verification platform with over 20 million app downloads worldwide, operates in a highly regulated environment emphasising security, privacy, and trust. Their senior, polyglot engineering team had been experimenting with AI-assisted development tools individually, but leadership needed to move beyond experimentation and understand how these tools could be applied safely, pragmatically, and at scale.

Beyond Autocomplete

Engineering teams needed to understand how modern AI tools perform in production environments, where agents add genuine value beyond basic code completion.

Governance in Regulated Industries

AI adoption in identity verification demands careful governance. Yoti needed practical guidance on balancing productivity gains with security, privacy, and cost controls.

Cutting Through Hype

With rapidly evolving AI tooling, Yoti needed a technically credible, vendor-neutral way to evaluate options and give their teams practical guidance grounded in real engineering workflows.

Our Approach

We delivered a full-day, hands-on technical workshop tailored specifically to Yoti's technology stack and regulatory context. The session combined live tool comparisons, agent-led workflow demonstrations, and practical frameworks, customised for Go/GRPC backends, mobile-native development, and the security considerations of a regulated identity verification platform.

Technical Solution

GitHub Copilot Deep Dive

Beyond basic autocomplete, demonstrating Copilot as a true pair programmer for production engineering workflows

CLI Tool Comparison

Live comparison of Gemini, Claude Code, Aider, and GitHub Copilot CLI with vendor-neutral evaluation against Yoti's real codebase

Agent-Led Workflows

Transitioning teams from prompt-based interactions to agent-led development workflows that handle multi-step engineering tasks

Testing & Evaluation Frameworks

Practical frameworks enabling Yoti to evaluate and iterate on AI tools independently, without ongoing external dependency

Regulated Industry Customisation

Workshop tailored for Go/GRPC backends, mobile-native development, and identity verification security requirements

Adoption & Cultural Change

Addressing the human side, building confidence and establishing governance for responsible AI adoption across 200+ engineers

The Impact

60%+
AI tool adoption
Engineering organisation actively using AI tools within 30 days of the workshop
Phase 2
Engagement secured
Three follow-up workshops commissioned, plus interest from external industry contacts
90%
Adoption target
Engineering adoption target set for Phase 2 completion, up from 60% baseline
Governance
Framework launched
Internal AI oversight and governance discussions initiated by engineering leadership

Within 30 days of the workshop, over 60% of Yoti's engineering organisation was actively using AI tools in their daily workflows, a dramatic acceleration from isolated experimentation to structured adoption. The workshop sparked internal governance and oversight discussions, with teams proactively planning deeper AI integration.

Demand for Claude Code and API access increased significantly. The success led directly to a Phase 2 engagement for three targeted follow-up workshops, with a target of reaching 90% engineering adoption.

Long-Term Value

AI-Enabled Engineering

Yoti's engineering teams now have practical, production-tested approaches to AI-assisted development.

  • Vendor-neutral tool evaluation framework for ongoing AI tool selection
  • Agent-led workflows replacing basic autocomplete across engineering teams
  • Testing frameworks enabling independent evaluation of new AI capabilities

Organisational Momentum

The workshop created lasting momentum beyond the technical skills transferred.

  • Internal governance and oversight structures emerging from engineering leadership
  • Phase 2 engagement extending adoption across specialist teams
  • Cultural shift from individual experimentation to coordinated, governed AI adoption

Ready to accelerate AI adoption?

We deliver hands-on workshops that move engineering teams from experimentation to structured, governed AI adoption.

Let's talk