Business value first
Every candidate workflow is scored against money made, money saved, risk reduced, or a bottleneck removed.
AI + Analytics Discovery
Find the AI workflows that actually advance the business.
LUMATARRA AI Discovery is built for companies that want practical AI inside advanced business processes - revenue, finance, operations, customer support, executive cadence, and knowledge work. We identify the highest-value workflows, prove feasibility, design controls, and ship the first useful version.
The point
AI does not create leverage until it changes the operating process.
Most teams already have the ingredients: Microsoft 365, Teams, documents, dashboards, meetings, CRM, finance systems, and overloaded people. The gap is the operating design that decides what AI should read, draft, route, alert, log, and escalate.
AI Discovery turns that gap into a short, evidence-based implementation path. Not a science fair. Not a generic roadmap. A ranked list of business processes, a feasibility readout, and a V1 workflow your team can use.
Smallest useful V1
We do not start with a platform rebuild. We start with the narrow workflow that proves operational value fastest.
Human control stays visible
AI can draft, summarize, classify, route, and alert. Sensitive decisions keep human approval and reviewable evidence.
Built where work already happens
Microsoft 365, Teams, Power Platform, Fabric, Power BI, Azure, and your existing business systems stay the center of gravity.
Advanced business processes
Where AI creates operational lift first.
The best candidates are repeatable, measurable, and tied to real decisions or handoffs. We prioritize the processes that make money, save money, or unblock the work that does.
Revenue operations
Turn CRM activity, pipeline hygiene, handoffs, proposals, and customer follow-up into measurable operating workflows instead of scattered reminders.
Finance and close
Use AI-supported intake, reconciliation prep, variance explanations, approvals, and exception routing to reduce manual close drag.
Operations and delivery
Expose capacity, status, blockers, owner drift, project risk, and missed commitments before they become leadership surprises.
Customer and support
Classify inbound requests, route work, summarize history, draft responses, and preserve approval controls for customer-facing communication.
Executive cadence
Convert meetings, scorecards, action items, risks, and decisions into a repeatable operating rhythm leaders can actually run.
Knowledge work
Automate document review, research, summaries, templates, SOP support, and institutional memory without losing human judgment.
Discovery flow
From process pain to working V1.
The work stays structured so it can move fast. We start with business value, verify the process and data reality, design the operating controls, then build the smallest useful workflow.
Stage 1
Process inventory
60-90 minutes
We identify the work that burns time, creates rework, slows revenue, or keeps leaders from seeing what is true.
Output
A ranked AI process opportunity map tied to business value, owner, current tool stack, and risk.
Stage 2
Workflow and data proof
2-5 business days
We verify systems, permissions, source data, documents, messages, and decision points so the idea can become a working workflow.
Output
A green/yellow/red feasibility readout with scope cuts, controls, and the smallest useful V1.
Stage 3
AI operating design
1 working session
We design how the AI layer will assist the process: what it reads, what it drafts, what it routes, what it logs, and where humans approve.
Output
A V1 operating design with owner map, approval points, audit trail, metrics, and implementation sequence.
Stage 4
First workflow build
30-day target
We ship the first useful version in the tools your team already uses, usually Microsoft 365, Teams, Power Platform, Fabric, Power BI, or Azure.
Output
A working AI-assisted process with evidence, handoff, training notes, and next-process recommendations.
What you get
A practical AI process map and a first workflow that proves value.
The deliverable is not a theoretical deck. It is a business-backed operating design with controls, evidence, and a path to implementation.
- Less manual status chasing, copying, pasting, summarizing, and routing.
- Clear owners, approvals, controls, and audit trails for AI-assisted work.
- Faster cycle time in the processes that affect revenue, cash, delivery, and customer experience.
- A Microsoft-aligned implementation path that IT can support and leadership can measure.
- A practical roadmap for the next 3-5 AI process wins after V1 proves value.
Common questions
Useful answers before you start.
What is AI Discovery?
AI Discovery is a structured process for finding and proving the best places to use AI inside business operations. It focuses on workflows, data, owners, approvals, and measurable business outcomes.
Is this an AI strategy project or an implementation project?
Both, but in the right order. We start with strategy only where it affects execution, then narrow quickly to a working V1 process that proves value.
What kinds of processes fit best?
Processes with repeatable intake, documents, messages, decisions, handoffs, status updates, approvals, exceptions, or reporting are usually strong candidates.
Do you replace people with agents?
No. The goal is to remove low-value coordination load so people can spend more time on judgment, customers, leadership, and execution.
Start AI Discovery
One conversation is enough to find the first process worth proving.
We will map the work, name the best candidates, and tell you where AI can create business value without overbuilding.