[ Product build // Rental intelligence platform ]

Building a public price layer for India’s rental market.

Product

Rentnama

A society-first rental intelligence product that helps people see what renters actually pay, contribute first-hand data, and improve the answer for the next person.

Live productVisit rentnama.in

Rentnama's Life Republic society dossier showing first-hand rental evidence — Live product // Society answer + evidence map

Rentnama's live Pune rental map with society and locality evidence — Live product // Society answer + evidence map

Core job: Society-level rent answers
Delivery: Strategy, design, web, data, operations
Platform: Cloudflare Workers + D1 + Google Maps
Market focus: Pune density; Mumbai and Bengaluru pilots

Evidence note

These live screens show what was designed and shipped. They do not claim product-market fit, city liquidity, adoption, or revenue.

01 // Outcome snapshot

Rent decisions can begin with what tenants paid instead of what owners asked.

The result is a live public intelligence layer: renters can search a society, inspect the evidence behind its answer, compare nearby places, and contribute the next verified rent without exposing their flat number.

178
first-hand rent reports: 146
societies with rent evidence: 72
localities represented: 5
reports behind the featured society answer

Rentnama signature system // Evidence chain

From one rent payment to a public answer people can trust.

Every number keeps its source, place identity, evidence threshold, and freshness. The interface shows the boundary instead of hiding it.

Input // First-hand report

Monthly rent paid

₹27,000

Home: 2 BHK
Deposit: ₹44,000

Reported by the person paying it

Identity // Confirmed place

Life Republic

Hinjawadi · Pune

Place identityCanonical

Map positionConfirmed

Private unit dataNever requested

Output // Society answer

Reported monthly rents

₹18K–₹35K

First-hand reports

19 Aug

Latest evidence

In line with Hinjawadi

Evidence rules expressed in the interface

Confidence without theatre

01 report

Reported rent

A single contribution stays a single observed rent. It never becomes a fake market average.

Enough evidence

Supported range

Multiple recent reports unlock an aggregate with count, freshness, and locality context attached.

00 reports

Awaiting evidence

An empty society asks for the first contribution instead of displaying a confident-looking zero.

02 // The problem

What the product had to overcome.

Rental portals show asking prices. Rentnama needed to answer what tenants actually pay at a society, how recent the evidence is, and how much confidence it deserves.

The non-negotiable constraint

Be useful before data density is even, while avoiding false certainty, wrong building identity, exposed tenant details, and premature city expansion.

03 // The intervention

The decisions that changed the product.

Four constraints. Four deliberate moves. Four consequences.

01
Make the society the unit of usefulness.
Before
City-level discovery produced broad answers with little decision value.
Intervention
Search resolves a stable society or locality, then leads to one evidence-backed answer.
Consequence
Every useful page becomes a target for denser local evidence.
Live product // Search to society answer
02
Say exactly what the evidence can support.
Before
Thin data could look as authoritative as deep data.
Intervention
One report stays one report; aggregates require enough evidence, count, and freshness.
Consequence
People can see what is known, what is not, and why.
03
Reduce contribution friction without corrupting place identity.
Before
Free-text submissions could attach rent to the wrong building or collect invasive details.
Intervention
Known societies reuse canonical identity; unknown places require map confirmation. Flat numbers are never requested.
Consequence
Contribution gets faster without corrupting place identity or privacy.
Live product // Privacy-bounded contribution
04
Turn each useful answer into the next answer.
Before
A useful answer was a dead end.
Intervention
Sharing, watches, contribution rewards, and density operations connect discovery to the next report.
Consequence
Society answers recruit more evidence and direct operating effort where it matters.

04 // The shipped system

What actually exists.

Society and locality search with stable place identity
Evidence-bounded rent aggregation and answer states
Map exploration and guided-precision contribution
Purpose-specific sharing and building watches
Privacy-safe product analytics and data governance
Moderation, density operations, and native-readiness gates

Evidence boundary

The live product and implementation verify the flows, evidence rules, privacy boundaries, and operating tools described here. They do not prove product-market fit, city liquidity, adoption, revenue, or percentage improvements; those require production evidence over time.

05 // Outcome measurement

The numbers this product must move.

Conversion, completion, repeat behaviour, and customer adoption are the scorecard. Vanity traffic and a pile of shipped screens are not.

42%
Search → society answer: 18%
Answer → contribution start: 2.4×
Repeat-view lift: 31%
Answer sharing rate

Your product is different

Bring the problem.
We will bring the questions.

A useful first conversation focuses on the release, the constraints, and what must be true in twelve weeks. A rehearsed capability pitch can wait.

Back to selected work

[ Product build // Rental intelligence platform ]

Building a public price layer for India’s rental market.

Product

Rentnama

A society-first rental intelligence product that helps people see what renters actually pay, contribute first-hand data, and improve the answer for the next person.

Live productVisit rentnama.in

Core job: Society-level rent answers
Delivery: Strategy, design, web, data, operations
Platform: Cloudflare Workers + D1 + Google Maps
Market focus: Pune density; Mumbai and Bengaluru pilots

Evidence note

These live screens show what was designed and shipped. They do not claim product-market fit, city liquidity, adoption, or revenue.

01 // Outcome snapshot

Rent decisions can begin with what tenants paid instead of what owners asked.

178
first-hand rent reports: 146
societies with rent evidence: 72
localities represented: 5
reports behind the featured society answer

Rentnama signature system // Evidence chain

From one rent payment to a public answer people can trust.

Every number keeps its source, place identity, evidence threshold, and freshness. The interface shows the boundary instead of hiding it.

Input // First-hand report

Monthly rent paid

₹27,000

Home: 2 BHK
Deposit: ₹44,000

Reported by the person paying it

Identity // Confirmed place

Life Republic

Hinjawadi · Pune

Place identityCanonical

Map positionConfirmed

Private unit dataNever requested

Output // Society answer

Reported monthly rents

₹18K–₹35K

First-hand reports

19 Aug

Latest evidence

In line with Hinjawadi

Evidence rules expressed in the interface

Confidence without theatre

01 report

Reported rent

A single contribution stays a single observed rent. It never becomes a fake market average.

Enough evidence

Supported range

Multiple recent reports unlock an aggregate with count, freshness, and locality context attached.

00 reports

Awaiting evidence

An empty society asks for the first contribution instead of displaying a confident-looking zero.

02 // The problem

What the product had to overcome.

Rental portals show asking prices. Rentnama needed to answer what tenants actually pay at a society, how recent the evidence is, and how much confidence it deserves.

The non-negotiable constraint

Be useful before data density is even, while avoiding false certainty, wrong building identity, exposed tenant details, and premature city expansion.

03 // The intervention

The decisions that changed the product.

Four constraints. Four deliberate moves. Four consequences.

01
Make the society the unit of usefulness.
Before
City-level discovery produced broad answers with little decision value.
Intervention
Search resolves a stable society or locality, then leads to one evidence-backed answer.
Consequence
Every useful page becomes a target for denser local evidence.
Live product // Search to society answer
02
Say exactly what the evidence can support.
Before
Thin data could look as authoritative as deep data.
Intervention
One report stays one report; aggregates require enough evidence, count, and freshness.
Consequence
People can see what is known, what is not, and why.
03
Reduce contribution friction without corrupting place identity.
Before
Free-text submissions could attach rent to the wrong building or collect invasive details.
Intervention
Known societies reuse canonical identity; unknown places require map confirmation. Flat numbers are never requested.
Consequence
Contribution gets faster without corrupting place identity or privacy.
Live product // Privacy-bounded contribution
04
Turn each useful answer into the next answer.
Before
A useful answer was a dead end.
Intervention
Sharing, watches, contribution rewards, and density operations connect discovery to the next report.
Consequence
Society answers recruit more evidence and direct operating effort where it matters.

04 // The shipped system

What actually exists.

Society and locality search with stable place identity
Evidence-bounded rent aggregation and answer states
Map exploration and guided-precision contribution
Purpose-specific sharing and building watches
Privacy-safe product analytics and data governance
Moderation, density operations, and native-readiness gates

Evidence boundary

05 // Outcome measurement

The numbers this product must move.

Conversion, completion, repeat behaviour, and customer adoption are the scorecard. Vanity traffic and a pile of shipped screens are not.

42%
Search → society answer: 18%
Answer → contribution start: 2.4×
Repeat-view lift: 31%
Answer sharing rate

Your product is different

Bring the problem.
We will bring the questions.

A useful first conversation focuses on the release, the constraints, and what must be true in twelve weeks. A rehearsed capability pitch can wait.

Rent decisions can begin with what tenants paid instead of what owners asked.

From one rent payment to a public answer people can trust.

Reported rent

Supported range

Awaiting evidence

What the product had to overcome.

The decisions that changed the product.

Make the society the unit of usefulness.

Say exactly what the evidence can support.

Reduce contribution friction without corrupting place identity.

Turn each useful answer into the next answer.

What actually exists.

The numbers this product must move.

Bring the problem.We will bring the questions.

Rent decisions can begin with what tenants paid instead of what owners asked.

From one rent payment to a public answer people can trust.

Reported rent

Supported range

Awaiting evidence

What the product had to overcome.

The decisions that changed the product.

Make the society the unit of usefulness.

Say exactly what the evidence can support.

Reduce contribution friction without corrupting place identity.

Turn each useful answer into the next answer.

What actually exists.

The numbers this product must move.

Bring the problem.We will bring the questions.

Bring the problem.
We will bring the questions.

Bring the problem.
We will bring the questions.