# AI Squad — Arithmiks **Your own AI team, for one business goal** > Markdown version of this page. Arithmiks is an AI-first software company based in Lahore, Pakistan. Contact: services@arithmiks.com You may know how AI could help your business. The harder part is deciding what to build, how to measure its value and who takes it to a working prototype. An AI Squad brings business and engineering together to deliver it. ## Why it matters **Almost everyone uses AI. Few make it count.** - **88%** of respondents use AI in at least one part of their business, yet the majority are still at the experimentation or pilot stage. (McKinsey State of AI, 2025 — https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2025) ## What is an AI Squad? **Good AI ideas stall. A squad keeps them moving.** Not a one-off AI project. The squad aligns your commercial goals with technical delivery. ### When AI projects lose momentum A good idea can still stall: tools applied without priority, experiments on unvalidated assumptions, and no engineering to take a successful test to production. Time goes into projects with no KPIs or measurable ROI. ### Focused and measurable The squad focuses on one defined AI opportunity. Market-fit criteria, system KPIs and ROI goals are set up front, then reviewed once the system is live. ### A real path to production As the work grows into a functional business system, senior engineers stay responsible for its architecture, quality and scalability, so a successful experiment becomes a production system that’s ready to scale. ## Meet your AI Squad **Architecture, engineering and design in one team** A single focused team covers architecture, engineering, and design. A system must be self-explanatory in its function. Those responsibilities are all embraced by your AI Squad. ### AI Architect Converts the business objective into a technical approach. The AI Architect defines system design, data flow, integrations, and guardrails, leading to a defined outcome. ### AI Native Engineers Develop, validate, and deploy the solution, applying AI at all engineering stages. They integrate it with your current systems and stress-test it in real-world situations. ### Designer The Designer clarifies workflows, interfaces, and human review points, so that your team understands and can utilize what they've created. ## Why act now **Standing still is a costly choice** AI is now a baseline, not an experiment. Arithmiks gets you to production first. We align your business goals to a leading industry solution, with security built in and a production-ready system delivered by senior engineers. ## The Arithmiks AI Squad **From objective to handoff** ### Stage 01 · Prioritise Market Fit (1–2 weeks) A team built around your goals **Core focus** Market fit · System KPIs · Workload vs. business goals · Success criteria **What you receive** - AI Squad formation — The right people, organised around your goal. - ROI metrics — How the system’s value will be measured. - Timeline — When each part of the work lands. ### Stage 02 · Build a Production-Ready System (3–6 weeks) Model and build the solution with AI-native skills. **Core focus** Solution modelling · AI-native development · Senior-led architecture · Quality and scale **What you receive** - Functional AI system — Built for real users, not a demo. - Scalability — Architecture that grows with demand. - Monitoring — Visibility into how the system performs. ### Stage 03 · Hand Off (1–2 weeks) Compare expectations with delivery, then hand over ownership. **Core focus** Engineering documentation · KPI review · Expectations vs. delivery **What you receive** - Expectation-to-results analysis — System KPIs and goals compared with what was delivered. - System handoff documentation — Everything your engineers need to own it. ## Outcomes & business impact **What changes for your business** ### AI investment focused on business goals ### Measurable progress against KPIs and ROI ### Production-ready systems for real users ### Senior engineers own quality and scale ### A clear handoff with docs and KPI analysis Ready to move an AI opportunity from planning to production? ## Real-world cases **Proven by industry leaders. Built for your team.** These examples show how top companies have used AI in their workflows, and how an Arithmiks AI Squad can build similar solutions for your team. ### Insurance claims processing Simple claims stall during catastrophe spikes. Allianz built AI agents that check coverage, weather, fraud and payouts, with human approval. - → Approval gates on policy data - → A dashboard showing the reasoning behind every payout ### Internal knowledge assistant Morgan Stanley backed its AI assistant with specific evaluation matrices and daily quality checks. - → Permissioned data pipelines - → Automated tests that catch errors - → Clean interfaces with precise sources ### Demand forecasting Legacy seasonal models couldn’t keep up with demand shifts. Walmart piloted machine-learning forecasting in some departments, then expanded it company-wide. - → Focus and scope first - → Models backtested on historical sales - → Scalable data pipelines - → An interactive review view for planners ### Legal research & drafting Legal teams need AI output they can verify. CoCounsel draws on trusted legal databases and links source citations inside document editors. - → Approved sources and access controls - → Drafting inside familiar apps like MS Word - → Every claim linked back to its source ### Inbound call capture Showroom teams were missing incoming call leads. Autotorino ’s AI captures calls, classifies intent and fills in CRM lead records. - → Call-handling rules mapped - → Speech-to-text connected to your CRM - → Instant lead alerts for your sales team ## FAQs **Questions we hear before week 1** **When should a business consider an AI Squad?** When your organisation is ready to commit to an AI initiative but needs support organising the work, defining measurable outcomes , developing the system or getting it ready for production. **Can the AI Squad take an initiative beyond experimentation?** Yes. The engagement includes production-level architecture and development , monitoring, KPI analysis and engineering handoff. **How is success measured?** By measurable ROI. The team works to your business objectives and system KPIs , and at handoff, expectations are compared with what was delivered and how the system performs. **How long does it take to move an AI project into production?** An AI Squad engagement takes 5 to 10 weeks: 1–2 weeks to prioritise , 3–6 weeks to build, and 1–2 weeks for handoff and training. **Who owns the AI system after handoff?** Your team does. You get the full source code repository, technical documentation , and spend and token-usage tracking , so your internal team can maintain it. ## Contact - Book a free AI consultation: https://arithmiks.com/contact - Email: services@arithmiks.com - Office: 537, C Block, Street 13, Faisal Town, Lahore, Punjab, Pakistan