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LatentView Analytics
AI-driven analytics, data engineering, and consulting for enterprises, including traditional, generative, and agentic AI projects across verticals.
Mid-to-large enterprises that want a specialist analytics firm to implement forecasting, pricing, customer, or data-platform AI inside an existing vertical process.
Buyers that want a packaged vertical SaaS product or a frontier-lab model API.
Verdict
Hire LatentView when you want a specialist analytics firm to implement AI inside an existing vertical process: forecasting, pricing, customer work, or the data platform under it. The firm sells AI-driven analytics, data engineering, and consulting, including traditional, generative, and agentic projects.
FY26 total operating revenue was ₹10,602 million, listed as $119.8 million in the company investor materials. The CEO said 28% of FY26 revenue was from AI projects visible to the client. This is a services company, so judge the team and the vertical, not a packaged product roadmap.
Score Breakdown
How LatentView Analytics scores on the jobs buyers hire it for, and on the company and commercial side of the deal.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Vertical analytics and AI implementation | Strong | The consulting job. |
| Data engineering for those projects | Strong | Sold beside the AI work. |
| Packaged vertical SaaS | Weak | A product license, not this firm. |
| Frontier-model API | Weak | A different vendor. |
Methodology
This page is an independent evaluation of LatentView Analytics for buyers comparing options in vertical ai consultancies. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. LatentView Analytics did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria sit under it in two groups.
- Buyer outcomes (for vertical ai consultancies)
- Vertical analytics delivery
- Data engineering beside the model
- Share of work visible as AI
- Public company scale
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.
Scope
LatentView Analytics is graded here as vertical ai consultancies. Criteria scores can move as more review volume and product checks are added.