For investors
ESI is building the personal decision layer.
Distribution has been validated experimentally. Now ESI is building activation, retention and monetisation.
Live product — My ESI + ESI Next
Ask · Compare · What-If — Live decision modes
Search experiment — Organic discovery already happened
1 founder — Built before forming a team
Public ESI pages are the world/context layer — not a substitute for product retention.
Built largely by one founder before graduating from BITS Pilani.
Speak with Vyom Experience ESI
Explore ESI in 15 minutes
- 01 The problem — Information is abundant. Personal guidance is not.
- 02 The product — Picture → Journey → ESI Next
- 03 One decision — Home purchase ripple
- 04 Why now — AI, data and search are shifting
- 05 Proof — Growth loop, distribution, early monetisation
- 06 Market & model — TAM / SAM / SOM and the economic engine
- 07 Competition — Context, not answers
- 08 Defensibility — Distribution, context, history, outcomes
- 09 Roadmap — The next 270 days
- 10 Founder / this round — Vyom Vyas
The problem
Information is abundant. Personal guidance is not.
Education → Career → Money → Health → Life
The missing layer: Who am I? What is happening? What should I do next?
What ESI is building
The ESI ecosystem
The world. Content · Tools · Calculators · Directories · Opportunities · Data.
My ESI — Your context.
You. Goals · History · Preferences · Documents · Decisions · Outcomes.
ESI Next
Ask · Compare · What-If. Ask · Compare · What-If. Decide → Save → Learn from outcome
The world around the decision + the context unique to you.
One Decision Ripple
Can I afford a ₹1.5 crore home?
An EMI calculator answers one number. ESI looks at the decision.
Money
Can I afford the EMI?
Liquidity
What happens to my emergency reserve?
Career
Can I still change jobs?
Investments
What would I need to liquidate?
Insurance
Does my protection need to change?
Retirement
Does another goal move?
Family
What else needs to be considered?
One decision. Your whole context.
Already built. Already being used.
- Career — Resume / JD intelligence (LIVE)
- Money — Finance experience (LIVE)
- Health — Health / directory experience (LIVE)
- My ESI — Personal context (LIVE)
- ESI Next — Ask · Compare · What-If (LIVE)
Why now
AI is finally capable enough
to reason across complex personal decisions.
Personal data is increasingly digital
but fragmented across platforms.
Search is becoming answer-led
making persistent context and a direct user relationship more valuable.
The experiment proved distribution. The work now is the decision layer people return to.
The growth loop we are building
Discover → Get utility → Add context → Decide → Return → Pay
Search has already demonstrated its ability to acquire attention. The current build is activation, repeat use and monetisation.
Distribution experiment
2.2K → 3.3K daily organic clicks during the Aug 1–7 experiment
Lesson: ESI demonstrated search-led acquisition without paid media.
Google Search Console · Web search · 1–7 August 2026
Early monetisation experiments opened multiple paths
Direct
Users moved from free utility to paid resume products through Razorpay.
Affiliate
Organic discovery generated Amazon STEM purchases.
B2B / transaction
A STEM lab referral opportunity has progressed toward closure, with ~₹1 lakh potential referral revenue. Pipeline — not realised revenue.
None of these is yet an optimised revenue engine. Together they show that ESI can monetise both personal intelligence and high-intent transactions.
The economic engine
Acquire — Free
Search · Content · Tools · Directories
Retain — My ESI + ESI Next
Persistent context · Decisions · Scenarios · Monitoring
Monetise — Subscription + high-intent transactions
Personal intelligence, reports, and products people already pay for.
Organisations → Education · Employers · Institutions · Partners
A large digital base. A focused entry point.
ESI does not need every internet user. It needs a small share of high-intent people whose decisions become more valuable when context persists.
TAM — 958M
India’s active internet users (2025). About 422M already use AI-enabled features — 44% of that base.
SAM — ~48M
Illustrative operating scenario: 5% of the active internet base entering recurring career, money, education and health journeys.
SOM — ~0.48M
Illustrative: 1% of that SAM over time, as ESI active profiles × expected ARPU.
At ₹3,000 blended annual value per user — an ESI working assumption, not a third-party forecast — SAM is ~₹14,400 Cr serviceable pool; SOM is ~₹144 Cr annualised potential.
Source: IAMAI + Kantar, Internet in India 2025 (Jan 2026). SAM/SOM figures are ESI operating scenarios so the assumptions stay visible and challengeable.
Competitive landscape
The field is crowded, but most players begin with a topic, product category or prompt. ESI begins with the person and the decision.
| Search | Generic AI | Vertical Apps | ESI | |
|---|---|---|---|---|
| Knows public information | Yes | Yes | Yes | Yes |
| Persistent personal context | Limited | Increasing | Within domain | Cross-domain |
| Decision-specific context | No | Prompt-led | Domain-led | Core architecture |
| Longitudinal outcomes | No | Limited | Some | Intended loop |
| Distribution surface | High | High | Variable | Existing ESI ecosystem |
ESI is not trying to beat general AI at general intelligence. It is building the permissioned context, decision workflow and outcome history around the individual.
Defensibility
Memory can be copied. The system around it is harder.
Distribution
High-intent public entry points
Context
Cross-domain, permissioned personal information
Decision history
What was considered, compared and chosen
Outcome learning
What actually happened after the choice
Generic AI can add memory. The more interesting asset is decision → action → outcome over time.
Personal because it has context. Trusted because you control it.
Permissioned
Only what the user chooses.
Purpose-aware
Only context relevant to this decision.
Reviewable
See and correct what ESI knows.
Revocable
Disconnect or delete context.
Privacy by design
Architecture designed around Indian data-protection requirements.
The next 270 days
0–90 days — Activation
Onboarding · product instrumentation · key context ingestion
90–180 days — Paid My ESI
Decision products · monitoring · first repeatable transaction paths
180–270 days — Cross-domain
Triggers · integrations · outcome learning · B2B pilots
Built from first principles.
Vyom Vyas. BITS Pilani — B.E. Electrical & Electronics, M.Sc. Mathematics, Minor in Data Science.
ESI was started while completing a final semester at BITS Pilani and built across product, AI, frontend, backend, cloud, analytics and distribution before forming a team.
Product · Frontend · Backend · AI · Cloud · SEO · Analytics · Deployment
No development agency. No large engineering team. No large marketing budget.
What this round unlocks
Activation
Turn discovery into My ESI profiles.
Retention
More useful journeys, decisions and monitoring.
Intelligence
Deeper context ingestion and cross-domain reasoning.
Monetisation
Subscriptions + high-intent transactions.
Team
Small product/data/GTM nucleus.
This round
Move ESI from demonstrated product + distribution experiments to measurable activation, retention and monetisation.
35% Product + AI
25% Growth + activation
20% Data / integrations
10% Infrastructure / compliance
10% Core team / operating buffer
What next
Distribution was the experiment. The product is the company.
Search helped us find information.
AI helped us ask questions.
ESI wants to help us decide what next.
ESI — Explore. Select. Innovate.
Ask one real decision. Speak with Vyom.