Step 1Start here
AI Readiness Sprint
Know where AI will pay off in your business, and what it will take.
- Use cases ranked by return and effort
- Review of your data and systems
- A 90-day roadmap with owners
- A clear go or no-go on each idea
AI integration and consulting for businesses worldwide
AI that fits your business, with guardrails built in.
Sprint AI Lab helps mid-market companies move from AI curiosity to working systems. We start with a two-week readiness sprint, build a pilot into the systems you already use, and keep cost and risk under control.
- Entry point
- Two-week readiness sprint
- Built into
- Your ERP, CRM and channels
- Always on
- Budgets, logs, human review
Illustration: agents run inside limits. Strays are stopped.
Three steps
A clear path from first idea to a system your team runs.
Start with the sprint. Move to a pilot when the numbers support it. Keep the system healthy with monthly operations.
Step 2
Pilot Build
One working agent, copilot or automation, built into the systems you already use.
- Integration with your ERP, CRM or channels
- Budget limits, logging and review points from day one
- Testing against your real cases
- Handover and training for your team
Step 3
Managed AI Operations
Keep what you built accurate, affordable and improving.
- Monitoring of quality and spend
- Tuning and model updates
- New use cases from your backlog
- A monthly review with your leadership
Pricing is scoped to your situation after a short call.
What we build
Practical AI, connected to the way you already work.
Most of the value comes from fitting AI into existing processes and systems. These are the four areas we build in.
Agents and workflow automation
Software that handles the multi-step work.
Agents read incoming requests, check them against your rules, and complete the task in your systems. Support triage, lead qualification, document processing and reporting are typical starting points.
Request arrivesEmail, WhatsApp, form
AI agentReads, drafts, decides
Policy checkBudget, rules, access
Your systemERP, CRM, inbox
Copilots on your data
Assistants that answer from your documents.
For customers, dealers or your own staff, with every answer traceable to a source.
Which warranty applies to a replacement pump?
It carries the remainder of the original warranty.Source: Warranty policy, section 4
Illustrative example
Integration
AI inside the systems you run today.
Secure connections through APIs, with access limited to what each assistant needs.
ERPCRMWhatsAppEmailWebsitesInternal tools
Data readiness
Get your information ready for AI to use.
We organise documents, spreadsheets and records so AI works from accurate, current information, with dashboards that show what it is doing.
Spreadsheets and PDFs
Cleaned and tagged
Searchable store
Dashboards and agents
Where we start
Operations-heavy businesses with real paperwork.
We focus on sectors where AI removes repetitive work and the return is easy to measure.
Quotes, orders and dealer questions still run on email, spreadsheets and phone calls.
Typical wins
- Quotation and order intake from emails and PDFs straight into your ERP
- Demand and inventory forecasts from your own sales history
- Maintenance and quality reports summarised for plant heads
- A dealer-support copilot grounded in catalogues and manuals
A good first pilot
Quotation intake. Requests arrive in many formats, the time saved is easy to measure, and the ERP connection proves the integration approach for everything that follows.
Patient enquiries, reports and billing follow-ups take more staff time than they should.
Typical wins
- Appointment and enquiry assistants on web and WhatsApp
- Report summaries prepared for clinician review
- Billing and claims follow-up workflows
- An internal assistant for SOPs and policies
A good first pilot
Enquiry handling with a clear handover to staff. Patient data needs extra care, so access control, data boundaries and audit trails are part of every healthcare build.
Support volume, catalogue work and returns grow faster than the team.
Typical wins
- Support agents for order status, returns and exchanges
- Catalogue enrichment and product copy at scale
- Review and feedback analysis for merchandising
- Shopping assistants on web and WhatsApp
A good first pilot
Order status and returns. Ticket volume gives a clear before-and-after measure, and decisions in retail tend to move quickly.
We also take on work in logistics, hospitality and other operations-heavy sectors.
Governance and cost control
The part most AI projects skip.
An AI system that works in a demo can still run up large bills or expose data in production. Every Sprint AI Lab build ships with these controls.
- Token budgets
- Spend limits per agent, per team and per run, set before launch.
- Circuit breakers
- Runaway loops and repeated retries are detected and stopped automatically.
- Access and data boundaries
- Each assistant sees only the systems and records it needs.
- Audit trail
- Every prompt, action and decision is logged and open to review.
- Human review points
- Sensitive actions wait for a person to approve them.
- Cost reporting
- A monthly view of usage and spend for each use case.
Agent run
Our method
Four stages, each with something you can see.
- 1
Discover
We map your workflows, talk to the people who do the work, and review your data and systems.
Sprint, week 1 - 2
Design
We rank the opportunities, design the architecture and guardrails, and agree a 90-day roadmap.
Sprint, week 2 - 3
Build
We build one pilot into your systems, test it on real cases, and train your team to run it.
Pilot, 4 to 6 weeks - 4
Operate
We monitor quality and spend, tune the system, and add the next use case.
Retainer, monthly
About Sprint AI Lab
Architecture first, from the first call.
Sprint AI Lab is led by Pritam Patil, a solution architect and consultant who integrates AI into the systems businesses already depend on.
That background shapes how we work. We start with how your operation actually runs, choose the smallest change that proves value, and build in the controls your finance and compliance teams will ask about later.
- Start small, measure early
- Every pilot has a target agreed before we build.
- Governance is part of the build
- Budgets, access rules and logs ship with the first version.
- Plain language
- You will always know what the system does and why.
Questions
Before you get in touch.
What happens in the AI Readiness Sprint?
Over about two weeks we review your workflows, data and systems, rank the AI opportunities by return and effort, and hand you a 90-day roadmap. You also get a clear go or no-go on each idea, so you can decide what to fund.
Do we need clean data before we start?
No. The sprint assesses what you have and shows what needs fixing first. Many pilots begin with a narrow set of documents or records and improve from there.
Which AI models do you use?
We choose for each use case, from the major providers and open models, based on accuracy, cost and data requirements. We design systems so the model can be swapped later without rebuilding.
How is pricing decided?
Every engagement is scoped to your situation, so we quote after a short call. Sprints and pilots are fixed scope, and operations run on a monthly retainer.
Start here
Book an AI Readiness Sprint.
Tell us a little about your business and what you would like AI to help with. We read every enquiry and reply by email.
- A short intro call to understand your goals
- A scoped proposal with a fixed price and timeline
- Sprint kickoff once you approve