AI Readiness, Architecture & Uplift
Your engineers use AI. The rest of your org doesn't.
You've bought Copilot or ChatGPT seats. A few engineers are flying. Product, QA, ops and design are still on 2022 tooling, and your AI architecture is whatever the last vendor sold you. We deliver three pillars in one engagement: a readiness audit, an AI architecture you can actually ship on, and a 4-week uplift across your entire SDLC and ADLC.
and inside every PADISO product, including Capitaly.ai and SearchFIT.ai. The problem
Sound familiar?
Every mid-market engineering org we walk into is stuck on the same five things.
We bought Copilot or ChatGPT Enterprise. Half the seats are dormant. Nobody's measuring uplift.
Two senior engineers are AI-native. Everyone else copies prompts in Slack and hopes for the best.
Product, QA, design and ops have no AI workflow. They're still on 2022 tooling.
Our AI projects keep stalling at PoC. Nothing makes it to production. The board is asking why.
We have an AI policy doc. We don't have AI in the actual SDLC. Legal is happy, delivery isn't.
The cost of "exploring AI" for another quarter.
Every month you stay in pilot mode, your competitors compound. AI productivity gains aren't linear. They're exponential, once teams get the workflow right.
Engineering throughput uplift left on the table when AI tooling is unevenly adopted.
Per year on AI seat licences with single-digit weekly active usage.
Quarters lost to "AI exploration" with no production output, no ROI, no playbook.
Senior engineers will leave for an AI-native team within 18 months if you don't catch up.
The fix
AI across the SDLC and ADLC, not just in the IDE.
Most "AI rollouts" are an IDE plugin and a Slack announcement. Two senior engineers fly. The rest of the org is unchanged. Six months later you have a productivity gap inside your own team.
We embed across your entire delivery chain. Engineering gets Claude Code, Cursor and Copilot wired into the actual workflow. Product gets AI-assisted discovery, specs and PRDs. QA gets generated tests and triage. Design gets v0 and Figma AI. Ops gets AI agents on incidents and on-call. Everyone learns on your codebase, your tickets, your stack.
The output isn't a deck. It's a measurable lift in cycle time, a working AI playbook your team owns, and governance that legal and the board can sign off on.
Three pillars in one engagement.
Most vendors sell you one of these. We sell all three because they only work together. A readiness report without architecture is shelfware. Architecture without uplift is a vendor lock-in. Uplift without strategy is a fad.
Pillar 1
AI Readiness
An honest audit of where your org actually is. Tooling adoption, governance maturity, data readiness, talent gaps, and an AI strategy the board can defend. We score you against scaled-up peers, not against a vendor's marketing slide.
- + SDLC and ADLC adoption audit
- + Governance, IP, data and risk baseline
- + Board-grade AI strategy document
- + Quantified ROI model and roadmap
Pillar 2
AI Architecture
The reference architecture you'll actually ship on. Model routing across Claude, GPT, Gemini and open-weight. RAG and agent patterns that survive contact with production. Evals, observability, cost controls, and an AI gateway so the team isn't pasting API keys into config files.
- + Multi-model routing and AI gateway
- + RAG, agent and tool-use patterns
- + Evals, guardrails, PII and prompt security
- + Cost, latency and observability tooling
Pillar 3
AI Uplift
A 4-week embed across engineering, product, QA, design and ops. Hands-on training on your codebase. Workflows wired into your delivery loop. A measurable lift in cycle time and a playbook your org owns when we leave.
- + Claude Code, Cursor, Copilot, v0 rollout
- + Role-by-role workflow embedding
- + Prompt library and evals on your stack
- + Cycle-time, throughput and quality measurement
The 4-week AI readiness program.
One month, one squad embedded with you, one outcome: every team in your delivery chain shipping with AI by week 4.
Week 1
Assess
Audit your SDLC and ADLC end to end. Interview engineering, product, QA, design and ops. Map workflows, score adoption, find the bottlenecks AI actually fixes.
Week 2
Integrate
Wire Claude Code, Cursor, Copilot and v0 into the actual delivery workflow. Set up evals, governance, prompt libraries and guardrails. Stop talking about AI, start using it.
Week 3
Train
Hands-on, on your codebase and your tickets. Engineers, PMs, QA leads, designers and ops all learn the workflow that fits their role. No generic vendor course.
Week 4
Optimise
Measure cycle time, throughput and quality lift. Tune workflows. Hand over a playbook your org can extend without us. Leave with governance that legal and the board accept.
What every team gets.
Not a generic "AI for everyone" workshop. Specific workflows, role by role.
Engineering
Claude Code and Cursor in the daily loop, AI-driven PR review, generated tests, refactor agents, codebase Q&A, and a prompt library tuned to your stack.
Product
AI-assisted discovery, PRDs and competitive teardowns. Customer-call summaries, theme extraction, and roadmap synthesis that takes hours instead of weeks.
QA & Test
Generated test suites, exploratory test agents, flaky-test triage, and bug reproduction from logs. QA stops being the bottleneck on every release.
Design
v0 and Figma AI for prototyping, AI-assisted design specs, and a design-to-code loop that ships in days, not sprints.
Ops & SRE
AI agents on incidents, log triage, on-call summaries, and runbook generation. Faster MTTR, less toil, fewer 3am pages.
GTM & Support
AI-drafted outbound, call analysis, ticket deflection and knowledge-base agents. Marketing, sales and support all run leaner.
Proven in the wild
Already shipping AI-native.
We've run this program inside scaling SaaS teams and inside our own product orgs. The playbook is live.
Embedded across the Ordermentum delivery org to lift engineering throughput, modernise the SDLC, and roll out AI workflows across product and ops.
Capitaly.ai & SearchFIT.ai
Both PADISO products are built AI-first using the same playbook. Every PR, every spec, every test pipeline runs through the workflow we'll set up for your team.
Who this is for.
Scale-up engineering orgs
20 to 200 engineers. You've bought the AI seats, but adoption is patchy and you can't point to throughput gains. You need consistent AI workflows across the whole team.
Mid-market companies under pressure
Health, Hotel & Hospitality, Retail, Logistics. Your competitors are leapfrogging on AI and the board wants a real plan, not another deck. We give you a working program in 4 weeks.
CTOs stuck in PoC purgatory
You've shipped 3 AI pilots in 6 months. Nothing's in production. We replace the pilot loop with a delivery loop, and leave you with governance and metrics the C-suite can defend.
Stop exploring. Start shipping.
Take the 5-minute AI Readiness Test, or book a 30-minute call. We'll tell you exactly where your team is and what 4 weeks would unlock.