AI Consulting That Ends With a Decision You Can Act On
You do not need a list of AI tools. You need to know which process is worth changing, whether your data can support it and what the first implementation should include.
SolvTreeAI provides operational AI consulting for growing businesses in India and the UAE. We are based in Mumbai, under Clivo Ventures Private Limited.
The problem with starting from a technology shortlist
A business can spend weeks comparing models or watching demos before anyone has named the problem. Meanwhile, the same quote is copied twice, the same approvals are chased and the same report is assembled by hand.
Consulting should connect a business decision to operational evidence. Sometimes the answer is AI. Sometimes it is a clearer process, a standard integration or better use of software already in place.
We start with the work, the information it depends on and the person who owns the result.
What the review covers
Operational discovery
Map how requests, records and decisions move through the business. Include the spreadsheets, messages and informal approvals that are absent from the official process diagram.
Use-case prioritisation
Compare opportunities by frequency, handling effort, data readiness, risk and the maintenance they will create. A high-volume task with unusable inputs may be a weaker first project than a smaller, well-defined workflow.
Build, buy or connect
Assess whether an existing product is sufficient, whether current tools need connecting, or whether a custom system is justified. Include exit options and recurring charges in the comparison.
AI system and agent boundaries
Define where a model helps, which source it should trust and which actions require approval. Clarify what happens when records disagree or the system cannot answer.
Pilot and measurement planning
Turn the chosen use case into a brief: inputs, outputs, owner, permissions, acceptance tests and a measurable baseline. Decide how the team will know whether to expand, change or stop.
What a useful consulting output contains
The exact deliverables belong in the agreed scope. For an operational planning engagement, ask for:
- A current-process map and a record of the main failure points.
- A ranked use-case list with the reasons behind the ranking.
- A recommended first scope, including what not to automate.
- A data and integration readiness checklist.
- Architecture options and build-vs-buy trade-offs.
- An evaluation and ownership plan for the first release.
- Implementation assumptions and recurring cost categories.
A presentation full of possibilities is not enough. The output should let your business approve a practical next step or decline the investment.
How the engagement works
Bring the people who do the work
The operating team, the decision-maker and the technical owner see different parts of the process. We need their input to distinguish an integration problem from a policy or data problem.
Inspect real examples
Work through representative requests, reports and exceptions with appropriate access controls. Redact sensitive information when it is not needed for the review.
Compare options and challenge the scope
A useful consultant should explain why a simpler option might be enough. We separate “possible to build” from “worth operating.”
Leave with a decision and an owner
The conclusion might be a pilot, a process cleanup, an existing-tool purchase or a larger system brief. Each needs a responsible person and a clear next action.
Industries and the decisions we help frame
- Freight/logistics: automate intake around the existing ERP or redesign job-cost workflows?
- Real estate: improve lead follow-up or first fix ownership and enquiry records?
- Contracting: connect estimates and site updates or scope a broader project operating system?
- Distribution: add reporting automation or resolve stock-data inconsistencies first?
- Hospitality: use a bounded guest-contact workflow or fix the underlying guest list and permissions?
- Travel: automate itinerary preparation or rebuild fragmented rate and booking records?
These are decision examples, not assumptions about what every company in an industry needs.
Evidence before recommendations
Our portfolio includes working systems and separately labelled designs. The agency-vs-in-house comparison explains one of the decisions an operational review may need to resolve. The AI-native ERP guide covers the choice between a working layer and a deeper rebuild.
Engagement and pricing
The scope depends on how many workflows, systems and stakeholders need review. Agree the questions to answer and the deliverables before setting the fee.
Consulting, implementation and ongoing operation are different pieces of work. Ask for them to be separated so you can assess the recommendation without assuming a build contract is required.
No fixed price is stated here. A review of one workflow and an organisation-wide roadmap require different effort.
Frequently asked questions
What is AI consulting for a growing business?
It is the work of deciding where AI can help, whether the required data and controls exist, and what a practical first implementation should include. The result should support a business decision rather than merely describe available tools.
Do we need an AI strategy before automating one workflow?
Not a large strategy document. You do need a clear process, an owner, a baseline and rules about what the system may do. A narrow review can establish those without delaying a useful pilot.
Can you help us decide between an agency and an internal team?
Yes. The decision depends on whether the need is a scoped operational build or a sustained development capability. It should also account for technical leadership, maintenance and knowledge transfer.
Can our existing developers build the recommendation?
That can be an option. If your team will implement, agree the required detail of the brief, architecture and handover in the consulting scope. Do not assume a high-level presentation is an implementation specification.
Do you only recommend systems that SolvTreeAI will build?
The review should compare existing tools, integrations and custom development. Any implementation offer should be separate from the recommendation so the business can evaluate the options on their merits.
How do you judge whether an AI use case is worth pursuing?
Look at the current operational cost, how often the task occurs, data readiness, risk and the cost of maintaining the proposed system. Use an agreed pilot measure before treating projected benefits as actual savings.
Make the first decision smaller and clearer
Bring the process that is causing repeated effort or missed work. We can help determine whether it needs AI, integration or a change in how it is run.