AI in software development
We move software organizations from AI pilots to AI-native delivery
Most AI initiatives stop at individual tools and isolated gains. We help software organizations design the operating model to unlock value and scale AI across the software development lifecycle.
Common challenges
Most organizations are stuck in one of two places
AI tools move individual developer output by 19%. Organizational throughput moves 3%. That gap does not close by adding more seats. It closes by redesigning the operating model.
Fragmented experiments
AI is already running across your organization in different tools, different teams, with no shared view of what is in the codebase or who owns it. Shadow usage rises faster than governance does, and that gap compounds every sprint.
You recognize this if your pilot count has outgrown your governance and your CISO is starting to ask the hard questions.
The assistant plateau
Copilot is deployed. Adoption numbers look fine. Developers write code faster. Cycle time hasn't moved. That's not an adoption problem, but rather a workflow problem. AI assistants make individuals faster - they do not change how work moves through testing, review, and release. The unlock is redesigning how work flows through the lifecycle, not adding more seats.
You recognize this if your AI rollout went smoothly, usage is real, and leadership is still asking the same question about throughput.
organizations has a formal AI strategy in place today
are in the process of building one, making tooling decisions before the strategy exists
have no strategy at all—the tools are running, nothing is governing them
Source: Eficode 2026 Report on AI adoption in software organizations (based on 270+ organizations in 5 survey waves)
Only 1 in 10 organizations has a formal AI strategy. Most are building the plane while flying it."
CHALLENGES
Why most AI programs stall
The blockers are structural, not technical. Across the organizations we work with, four patterns account for the vast majority of stalled AI transformations.
EU AI Act max fine for prohibited practices. Enforcement has been active since 2025, and exposure scales with how much unmanaged AI is already in your pipeline.
EU AI Act, 2025
Organizational throughput improvement, against 19% individual productivity gain. Deploying more tools doesn't close that gap.
DORA, 2025
Enterprise GenAI usage through personal accounts — outside your compliance boundary, outside your audit trail.
Netskope, 2025
Organizations running AI on sovereign infrastructure. 59% are entirely on public cloud.
Eficode 2026 report
The bottleneck effect
Faster code output means more code waiting longer for testing, review, and sign-off.
Most organizations accelerate development and then find that requirements, compliance, and release are exactly where they left them. You haven't sped up the pipeline. You've moved the queue further down it.
How we work
The path isn't a mystery. The governance usually is.
Most organizations know where they want to get to. What is harder to see is where they actually are and what is blocking the next step. We identify the constraint, move you one stage forward, and build the governance to hold it. That is what makes the next stage reachable.
The organizations that will win are not necessarily the ones moving fastest today. They are the ones building the right foundations.
Stage
Experiment
You can't scale what you can't see, and you can’t govern what you can’t measure. This stage maps what AI is actually doing in your organization: what's in use, what's generating value, what's generating risk, and where the actual bottleneck is that everything else depends on.
Services
AI Accelerator Program
In eight weeks, we take you from fragmented assistants to two or three governed, production-running agents, and with a 12-month roadmap to scale.
AI Tool Adoptions
This engagement deploys the right coding and product AI tools across your engineering organization, runs role-based training cohorts, seeds AI Ambassadors, and measures actual productivity impact.
AI Readiness Assessment
The assessment gives you a benchmarked view of where your organization stand: a prioritized 12-month roadmap and an ROI business case your CFO can challenge and pass.
Client story
DNA
Piloting AI-assisted coding at DNA
DNA realized significant benefits through partnering with Eficode and adopting GitHub Copilot.
The results include improved code development efficiency, elevated code quality, and enhanced collaboration.
Eficode's expert guidance, seamless integration, and continuous improvement maximized value for DNA.
Some of the most important drivers in improving our capability to provide valuable digital services are the developers’ satisfaction and flow state in their work. We want to learn how to improve developer experience with AI-powered tools.
Stage
Automate
This is where AI moves out of individual workflows and into the delivery pipeline. Agentic workflows are designed, tested, and put into production with governance built in from the start, not retrofitted after the first incident.
Services
DevOps and Quality Automation (AI)
This engagement combines DevOps consulting and continuous quality assurance into one. It helps your organization accommodate delivery for the AI-enhanced software development.
Agent Creation in Selected Tech
We build the first agents alongside your team, in your chosen tech stack, on your real SDLC workflows. Your engineers learn the patterns, governance requirements, and delivery discipline firsthand.
AI FinOps and Governance
We deploy the AI Token Insights platform, giving you full visibility into AI spend across teams, repositories, users, and models, with anomaly alerts, ROI attribution, and monthly expert guidance
Client story
Sennheiser
From four months of testing to one week
After connecting the delivery toolchain and automating what had been entirely manual work, test cycle time dropped from three to four months down to a single week. Resource optimization improved 300%.
The productivity improvement was 2-3x. That's capacity we've reinvested.
Stage
Integrate
Early wins stop being isolated and start compounding. The system of record connects to the system of delivery,and AI finally has the context it needs to be useful at scale, not just fast for the individual.
Services
Expert AI Resources and Projects
Our consultants are embedded in your engineering organization, working on your actual backlog, adapting to what's blocking production rather than executing a pre-agreed plan.
Agent Orchestration Platform
The platform builds the governed core that connects agents: identity and policy, observability and cost tracking, audit and trace — within your current primary partner stack today, but extensible.
Client story
Air France-KLM · Aviation
Rovo AI for 90,000 people on day one
Moved 90,000 users to Atlassian Cloud and activated Rovo AI at go-live, treating the migration as an AI readiness project from the outset rather than a platform swap.
Now we have more non-developer users on Atlassian than developers. They see how it could improve their life.
Stage
Transform
The toolchain isn't what changes here. The organization is. How teams are structured, how decisions get made, what delivery looks like when AI is part of every stage. Organizations at this point have stopped asking whether AI works and started building for what comes next.
Services
Agile, Portfolio and ITSM AI Adoption
A transformation engagement that redesigns how your organization plans, delivers, and operates software, embedding AI into your workflows.
AI Center of Excellence
We design and set up the operating model, governance framework, intake processes, and roles that make AI investment sustainable at scale.
Client story
Crédit Agricole CIB
New applications in hours, not days
After moving to GitLab, time to delivery for new applications went from days to hours. The change reached everyone who touches the delivery cycle, not just developers.
A structural change, not a productivity trick.
Common questions
Start here
One conversation. One page of output. No commitment.
The AI Maturity Assessment takes 30 to 45 minutes. It tells you which failure mode applies, where the biggest bottleneck is, and what to address first.