AI implementation consulting Turn AI ambition into real business impact scaled - Avenga

Accelerate software delivery by 50% with AI embedded across your SDLC

Most organizations stop at individual AI tool adoption, capturing 10–20% productivity gains per person. We help enterprises close that gap, embedding AI across the entire SDLC that enables 50% faster software delivery.

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Your teams have a clear picture of the project scope, with AI reducing estimation effort by 40-60% and supporting informed decisions across teams.

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Requirements are structured into traceable user stories. AI delivers ~30% efficiency gains and enables your teams to stay fully aligned each sprint.

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Your experts work with comprehensive design guidance, in which simulated user behaviour and Figma-to-frontend scaffolding cut rework by 25-30%.

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Architectural decisions are made with clarity and maintained with consistency as AI analyzes your codebase, increasing efficiency by 25-30%.

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Automatic code suggestions and test generation free your team for high-value work — with ~20% faster workflows.

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AI generates test scenarios from requirements and predicts which tests matter most — scaling your QA process 25-30% faster.

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25-40% faster incident resolution is achievable when AI surfaces relevant history and context the moment an incident occurs.

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What is Avenga Intelligent Flow?

Avenga Intelligent Flow is where AI stops being a pilot project and starts driving efficiency across every stage of your SDLC. A structured program that embeds standardized AI usage across your software devlivery and aims to foster long-term human-agent collaboration.

Establish your AI productivity baseline

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We measure squad-level productivity, standardise AI tooling, and form a cross-functional team to own the programme from the inside. You finish this phase with a clear picture of where you stand and a concrete roadmap for what comes next.

Connect AI to SDLC at every level

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We build knowledge bases from your documentation, connect AI to your core SDLC systems, and introduce role-based assistants for every function in your delivery team. Your teams work with tools that are aligned with your product and your processes.

Scale human-agent collaboration

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Agentic workflows are introduced across architecture, security, testing, and infrastructure, orchestrated into a unified layer that grows with your organisation. Your delivery capability compounds in value the longer the programme runs.

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The difference behind our AI delivery

40-60%

Efficiency boosts can be realized through a fully embedded, AI-native SDLC.

97%

Of organizations choose to continue their journey with Avenga after the first project.

250+

Data and AI specialists dedicated to your excellence and innovation.

Why Avenga

  • AI for every role in your delivery team

    Role-based assistants are introduced for every function across your SDLC, from Product Manager to DevSecOps. Every team works with AI agents that understand their context and workflows.

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  • Collaboration with an ISG-recognized leader

    Avenga has been named Europe's Rising Star by ISG for its data and AI capabilities, recognized for redefining the market's perception of customer-centricity in AI development services.

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  • Compliance-by-design

    Innovate within the world’s most restricted industries without compromising on speed. We embed guardrails directly into your SDLC core, turning regulatory requirements into a competitive advantage.

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  • Scalable and agile AI enablement

    Avenga moves at the speed your delivery teams need. Our commercial models are flexible, milestone-aligned, and built around your SDLC outcomes — so you get enterprise-grade AI capability and stay nimble at every step.

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FAQ

Individual AI tool usage is a starting point, not a strategy. Without shared context, defined workflows, and measured outcomes, productivity gains stay uneven and unmeasured. Avenga Intelligent Flow offers a structured approach. It ensures your organisation captures value at the team level, not just for the individuals who happen to experiment most.

Adoption is designed to be incremental, not disruptive. We introduce AI maturity in stages (starting with the tools and workflows your teams already use) and continue to move on from there. Role-based assistants are introduced gradually, with each stage validated before the next begins. Your teams stay productive throughout.

Generic AI tools struggle with complex, context-heavy environments. That’s why we build dedicated knowledge bases grounded in your requirements, architectural decisions, and codebase. The more complex your environment, the more value a context-aware approach delivers.

Compliance and security are integral to our AI-native SDLC approach. Governance, audit trails, and access controls are embedded into the delivery model from the start. We work within your frameworks and make the boundaries explicit before anything is deployed.

The first stage is designed to produce a clear baseline and early, measurable productivity signals within the first 1–3 months. This is where we measure squad-level productivity, standardise AI tools, and lay the foundation for what comes next. From months 3–6, deeper gains begin to compound as we introduce role-based assistants across every function. From month 6 onwards, the full agentic layer is on. Autonomous workflows for architecture, security, testing, and infrastructure are introduced, and your teams begin the shift from human-to-assistant-to-agent.

Capture the benefits of AI in software development lifecycle 

Engineer the future with AI-native SDLC.
Our initial discovery call is structured around your SDLC objectives, constraints, and data maturity, covering:

1. Expert validation of where real gains are possible in your SDLC
2. Workflow optimization adjusted to your technical context
3. KPI mapping to measure the transition from manual to autonomous cycles

Let’s find your starting point — contact us.

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