Question 1

Will AI replace software developers?

Accepted Answer

No – AI SDLC enablement makes your engineers faster, not obsolete. AI handles repetitive tasks like code analysis and test generation, while senior engineers retain ownership of architecture, security, and review decisions.

Question 2

How do you measure the ROI of AI in software development?

Accepted Answer

We track concrete before/after metrics – PR review time, test coverage, deployment frequency, and change failure rate (DORA metrics) – so ROI is based on measurable delivery outcomes, not subjective productivity claims.

Question 3

Does this work with our existing tech stack and tools?

Accepted Answer

Yes – we take a vendor-agnostic approach. We audit your current stack first, then integrate AI tooling that fits what you already use, rather than requiring a platform switch or a specific toolset.

Question 4

How long does it take to implement AI in our SDLC?

Accepted Answer

Most teams start with our Pilot package, which delivers a working, measurable result in about 2 weeks for a single squad and one pipeline focus area – from the initial SDLC audit through AI tooling integration, hands-on enablement, and a velocity baseline you can measure against. If you're ready to move beyond one squad, Accelerator extends AI across two focus areas for a full product team in 3–4 weeks, and Scale covers multi-team, multi-pipeline rollout with private deployment in 5–6 weeks. In every case, the timeline follows the same fixed-scope, fixed-price delivery model – Assessment, Integration, Enablement, Measurement – sized to how much of your pipeline you're transforming.

Question 5

Is our code and data safe when using AI tools in development?

Accepted Answer

Security and governance are non-negotiable – tooling integration follows DevSecOps principles, keeps all AI-assisted code under the same review standards as manually written code, and every engagement is covered under NDA.

Question 6

Can this be used to assess a portfolio company before investing?

Accepted Answer

Yes – the same audit methodology is used in our technology due diligence engagements to assess AI-readiness, code quality, and delivery maturity of target companies pre-investment or pre-exit.

Question 7

Will this disrupt our current sprint cadence?

Accepted Answer

No – the assessment and pilot run alongside your existing sprints. We work within your current cadence and ceremonies, introducing changes incrementally so delivery never stops during the engagement.

More than faster code. AI embedded across the entire SDLC.

AI in the SDLC. Less technical debt, more predictability.

Writing code faster without the right processes just shifts risk downstream.

Start with proof. Scale when it's working.

Pilot

Accelerator

Scale

From assessment to measurable velocity

SDLC Audit (Assessment)

AI Tooling Integration

Pilot Enablement

Velocity Baseline (Measurement)

AI SDLC enablement we've already delivered

SaaS Scale-Up Platform Modernization

FinTech AI-Assisted Delivery Enablement

Industrial Software Delivery Transformation

Built for delivery. Backed by engineering.

AI-assisted, human-led

Deep engineering capability

Fixed scope, fixed timeline

Full SDLC coverage

Vendor-agnostic tooling

Outcome-first delivery

One fixed-price package

We prove it in results

Altimi Modernization & AI Team

Is your team ready for AI agents?

Governance from day one

Measurable results

AI-readiness audit

Proven agentic patterns

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