We help enterprise leaders answer the hardest AI questions — what to build, in what order, with which technology, and at what cost — in 2–4 weeks. Hard deliverables, actionable roadmaps, zero buzzword fluff.
Enterprise AI projects fail for strategic reasons more often than technical ones. These are the patterns we see — and solve — every day.
"We started building before we knew what to build — 14 months and $2M later, we have nothing in production."
"Every vendor wants to sell us their platform. We can't get objective advice on what's actually right for us."
"We have 20 AI ideas and no framework to decide which ones to fund first."
"Our board approved AI investment but our CFO wants a credible ROI model before we spend anything."
"We hired a big consulting firm. They gave us 200 slides and zero decisions. We're back to square one."
"Our data isn't ready but we don't know what 'ready' actually means or how long it will take to get there."
Every one of these problems has a structured answer. The difference between enterprises that win with AI and those that don't isn't talent or budget — it's whether they made good decisions early. Our consulting engagements exist to give you those decisions fast, based on your actual data, systems, team, and business context — not a generic framework.
We've consulted on AI strategy for enterprises across healthcare, finance, manufacturing, legal, and retail. We know what works, what doesn't, and how to sequence investments to get to measurable ROI in the shortest possible time.
Every deliverable is a decision-ready document — not a framework overview. You can take any one of them to your board, your engineering team, or a vendor RFP and use it directly.
A scored audit of your organisation across four readiness dimensions — each with specific gaps identified and actionable remediation steps.
Every potential AI use case scored across five dimensions: ROI potential, data feasibility, implementation complexity, time-to-value, and strategic alignment.
For each major AI capability identified, we evaluate whether to build custom, buy a platform, or partner — with honest tradeoff analysis and a clear recommendation for your context.
Specific, named technology recommendations — which LLM, which vector database, which orchestration framework, which cloud provider — with the reasoning behind every choice explained clearly.
A sequenced delivery plan that tells you exactly what to build, in what order, with what team, on what timeline — tied to measurable business outcomes at every milestone.
A realistic financial model covering every cost category — development, inference, infrastructure, maintenance, and team — with 3-year projections, sensitivity analysis, and a CFO-ready summary.
Every industry has unique data, compliance requirements, and performance benchmarks. Here's how we apply custom AI development across key verticals.
Ideal for: Executives who need to make a fast go/no-go decision on AI investment
Ideal for: Enterprises ready to commit to a multi-quarter AI program
Many clients use our consulting deliverables to run competitive vendor RFPs, guide in-house development teams, or build internal business cases. Our strategy work is fully independent. We give you the best advice for your organisation — not the answer that benefits us most.
A structured, intensive engagement designed to give you everything you need to make confident AI investment decisions in 30 days or less.
We run structured interviews with your CTO, COO, department heads, and data team. We review your existing data infrastructure, systems architecture, team capabilities, and any previous AI attempts. This is where we learn what you've tried, what failed, and why.
We run a facilitated workshop with your business and technical leaders to surface all potential AI use cases. Each opportunity is then scored independently by our team using a five-factor framework: ROI potential, data feasibility, implementation complexity, time-to-value, and strategic alignment.
For each prioritised use case, we evaluate the specific technology decisions — which LLM, which vector database, which orchestration framework, which cloud provider. For each major capability, we run a structured build vs. buy analysis with 3-year TCO comparisons. Where "buy" is recommended, we produce a vendor shortlist with evaluation criteria.
We translate all prior analysis into a sequenced 12–24 month delivery roadmap with phase gates, team requirements, and business outcome targets for each phase. Simultaneously, we build the TCO model — a complete 3-year financial picture covering development, inference, infrastructure, and maintenance costs, with conservative, base case, and optimistic ROI scenarios.
We present all deliverables in a structured readout session with your leadership team. We walk through each finding, answer questions, and facilitate the decision conversation. You leave the session with a clear understanding of what to do next, in what order, and what it will cost. All documents are transferred to you in editable formats.
Hard, specific outputs you can use — not narrative frameworks dressed up as strategy documents.
We don't deliver a generic "AI maturity model" and ask you to self-assess. We tell you exactly where you are, exactly what's blocking you, and exactly what to do about it. Every recommendation is specific to your organisation, your data, and your constraints.
Our TCO model includes bottom-up cost estimates for every line item — development hours, compute costs, API pricing, infrastructure, and team. We show our working and provide sensitivity analysis so your finance team can stress-test every assumption.
Whether you implement with us, with another vendor, or in-house, the roadmap works. It's structured around outcomes, not vendor capabilities. It tells any engineering team exactly what to build and in what sequence.
We are model-agnostic and vendor-agnostic. When we recommend Claude over GPT-4 for a use case, we explain why — and acknowledge where GPT-4 would be better. Our recommendations reflect your best interests, not any vendor relationship.
Decisions made, investments unlocked, and programs launched — directly from our consulting engagements.
" We had 20 AI ideas and no way to choose. Aeologic ran a 4-week deep dive that cut our list to 3 priority initiatives with clear ROI cases. The TCO model was so rigorous our CFO approved the budget on the spot without asking a single follow-up question.
Chief Digital Officer, NBFC — Mumbai
" We were about to spend ₹3Cr building a custom LLM platform. The consulting engagement showed us we could achieve 90% of the same outcome with an existing solution in 8 weeks. That single insight paid for the consulting 15 times over before we wrote a single line of code.
VP Technology, Healthcare Network
" Our board wanted to see a credible AI strategy before committing capital. The roadmap and TCO model Aeologic delivered were exactly what we needed. Board approved the program unanimously and we were in production on the first initiative within 6 weeks of the engagement closing.
CEO, Mid-size Manufacturing Enterprise
How we compare to the three alternatives enterprise leaders typically consider.
Everything enterprise decision-makers ask before working with us — answered directly and thoroughly.
An Aeologic consulting engagement includes: an AI readiness assessment (scored audit across data, technology, team, and process dimensions), use case identification and ROI prioritization (ranking AI opportunities by business value, feasibility, and time-to-value), a build vs. buy analysis for each major AI capability, specific technology stack recommendations with named tools and vendors, a sequenced 12–24 month AI roadmap tied to business outcomes, and a Total Cost of Ownership model with realistic 3-year budget projections. All six deliverables are included in the 4-week deep dive format.
We offer two formats. The 2-week AI Strategy Sprint (₹8–15L / $9,500–$18,000 USD) delivers an AI readiness assessment, top-3 opportunity analysis, and an executive briefing deck — ideal for organisations needing a fast go/no-go decision. The 4-week AI Deep Dive (₹20–40L / $24,000–$48,000 USD) delivers all six deliverables including the full prioritization matrix, build vs. buy analysis, technology recommendation, 12–24 month roadmap, and TCO model — ideal for organisations ready to commit to a multi-quarter AI program.
Yes, absolutely. Our consulting engagements are fully independent of any development work. Many clients use our deliverables to run competitive vendor RFPs, build internal business cases, guide in-house development teams, or take to their boards for budget approval. There is no obligation to proceed with us for implementation — and we never compromise the quality of our advice to create development work for ourselves. We give you the best recommendation for your organisation, full stop.
An AI readiness assessment is a structured audit that evaluates how prepared your organisation is to benefit from AI investment. It covers four dimensions: data readiness, technology readiness, team readiness, and process readiness. Without this assessment, enterprises routinely invest in AI initiatives that fail because of preventable infrastructure or data gaps — not because the AI technology doesn't work.
AI consulting focuses on strategy, decisions, and direction — answering what to build, in what order, with which technology, and at what cost. An AI engineer focuses on building. The best AI programs start with consulting to establish a rigorous roadmap, then transition to engineering to execute it. Skipping the consulting phase is one of the most common reasons enterprise AI projects fail.
Yes, genuinely. We are model-agnostic and vendor-agnostic. We work with Claude, GPT, Gemini, open-source LLMs, and every major cloud provider. When our analysis shows that a client's best option is to use an existing SaaS platform rather than build custom, we say so — even when that means less implementation work for us.
All clients receive 90 days of follow-up Q&A support after the engagement closes. If you decide to proceed with implementation, we can seamlessly transition to an engineering engagement without any knowledge ramp-up, since our consultants have full context of your systems and priorities.
We sign a comprehensive NDA and Data Processing Agreement before any discovery work begins. All information shared during the engagement is treated as strictly confidential. All documents and data are stored in encrypted, access-controlled systems, and can be deleted from our systems upon written request after the engagement closes.
Tell us where you are and what decisions you need to make. We'll propose the right engagement format, timeline, and cost — and explain exactly what you'll have at the end.
Speak directly with a senior AI strategist who has delivered real AI programs — not a sales rep.
Scope, deliverables, timeline, and fixed cost — in writing, within one business day of your consultation.
Once contracts are signed, stakeholder interviews begin within 5 business days. No waiting list.
We respond within 4 business hours.
Your information is protected and never shared.