AI Consulting Services: find the use cases worth building
A practical audit of where AI can save time or money in your business, what to build, what to buy, and what it will cost to run.
Most owners we speak to have been told they need AI. Few have been told where, how much it will cost, or what to do first. Our consulting work answers those three questions in plain language, with a short written plan you can act on or hand to any vendor.
Because we also build software, we can tell you what is realistic to implement and what will need heavy engineering. We do not sell licences or take commissions from tool vendors. If the answer is 'buy a subscription and do nothing custom', that is the advice you get. Our report is written for owners and managers, not engineers, with costs in rupees.
Questions that bring teams to AI consulting
Too many ideas, no priority
Staff suggest chatbots, forecasting, auto-replies and document reading. Without a ranking by value and effort, the team picks whatever sounds exciting and not what pays back.
Build or buy is unclear
A ready tool may cover seventy percent of your need for a monthly fee. A custom build may fit better but cost more. The right choice depends on volume, data sensitivity and how special your process is.
Data and process are not ready
AI cannot fix a process nobody has written down or data scattered across WhatsApp and paper. Readiness gaps must be found before money is spent on models.
Fear of runaway cost and risk
Usage-based pricing, vendor lock-in, privacy questions and wrong answers all worry owners. These are manageable, but only if designed in from the start.
What our AI consulting engagement covers
Use-case audit
We interview teams, map repetitive and text-heavy work, and list candidate use cases. Each is scored on time saved, error cost, data availability and implementation effort.
Build vs buy analysis
For the top use cases we compare ready tools, low-code automation and custom builds, with the monthly and one-off cost of each over a year and what you would be locked into.
Data and process readiness check
We review where your data lives, how clean it is, who can access it and which parts of the process are undocumented. You get a short fix list that comes before any AI work.
Cost model and usage limits
An estimate of model usage and hosting cost at your expected volumes, with caps, caching and cheaper-model options. You see running cost before you commit to build.
Risk and privacy review
What data would leave your systems, which provider terms apply, where a wrong answer would hurt, and which steps need human approval. We flag legal questions for your own adviser.
Roadmap and pilot plan
A staged plan: one small pilot with a success measure, then a decision point. The document is yours and can be executed by us or by any other team.
How an AI consulting engagement runs
Discover
Short interviews with owners and team leads, plus a look at the tools, data and documents you use daily. We watch real work, not only hear descriptions of it.
Define
We turn findings into a ranked list of use cases, each with an expected benefit, effort and risk, and agree with you which two or three to examine closely.
Design
For the chosen use cases we sketch how the solution would work, who would use it, and where a human stays in the loop.
Build
Where useful, we run a small proof of concept on your real samples, so the recommendation rests on test results instead of vendor claims.
Ship & extend
You receive the written report, cost model and pilot plan. You may implement with us or anyone else, and we can review a third party's proposal if asked.
What it costs
Consulting is scoped by number of teams and use cases, and is priced as a fixed fee. If you go on to build with us, the closest anchor is ₹1,00,000 for AI chatbot and automation work.
- Number of teams and processes reviewed
- Depth of proof of concept
- Data volume and sensitivity
- Workshop time on site or online
- Roadmap and cost-model detail
All prices exclude 18% GST. See also website costs and app costs.
Questions we get asked
What do we receive at the end?
A written report with ranked use cases, a build-or-buy recommendation for each, a data readiness list, an estimated running cost and a pilot plan. It is yours to keep and use with any vendor. We also include a short summary that you can share with partners or your board.
Are you neutral on tools?
We have no resale or commission arrangement with any AI vendor. We recommend what fits your volumes and budget, including off-the-shelf products we do not build, and we give reasons that you can check yourself.
Do we have to hire you to build afterwards?
No. The plan is written so another team can execute it. Many clients do ask us to build the pilot, but that is a separate decision with a separate fixed quote. Every recommendation in the report stands on its own and does not assume you will hire us.
How long does it take?
It depends on how many teams are involved. A single-department review is usually a short exercise, and a company-wide audit takes longer. We give a timeline in the written quote after the free discovery call.
Can you help us control AI costs we already pay?
Yes. We review current subscriptions and API bills, find duplicated tools and heavy prompts, and suggest caching, cheaper models for simple tasks and usage limits. Savings depend on how you use the tools today. We do not take a share of any savings, so our advice is not tied to selling you something.
Will you tell us if AI is not worth it for us?
Yes. For some processes the honest finding is that a spreadsheet, a rule or a better form removes the pain. We would rather say that than sell a build that does not pay back. A short, honest negative finding is a successful outcome of the engagement.
Ready to scope it?
Tell us what you want to build. You get a fixed written quote after a free discovery call.