Research domain value like a market desk, not a registrar form.
DomainFlip AI brings valuation, availability, comparable sales, resale status, and acquisition planning into one place, so you can judge a name, not just look it up.
Valuation engine
Combines a trained ML model, comparable sales, RDAP history, and TLD benchmarks into one defensible price range.
Market data
Works from reported sales, TLD medians, and category trends in a local dataset instead of a single unexplained number.
Acquisition workflow
Turns a score into a target price, a budget, a watchlist entry, and a clear buy, watch, or avoid call.
Example Analysis Chain
Value formation trace
01 · Input
primeagent.ai
Normalized and categorized
02 · ML
₹1.52L
Baseline from historical pattern match
03 · Comps
₹1.34L
Weighted nearest observed sales
04 · Decision
Watch
Acquisition depends on price discipline
.com liquidity
High
Broadest exit path for commercial buyers
.ai pricing
Firm
Premium demand in AI/startup categories
Opportunity band
₹15k-₹80k
Where mispriced names are easiest to surface
Sample Workspace
Candidate pipeline with pricing, posture, and next action
See which names deserve capital, which ones deserve monitoring, and which ones should be dropped.
| Domain | Score | Value | Status | Action |
|---|---|---|---|---|
| northforge.ai | 84 | ₹2.03L | Taken | |
| gridmint.com | 78 | ₹1.62L | Taken | |
| fluxpilot.io | 72 | ₹96k | Taken | Buy |
| techtics.in | 54 | ₹8.2k | Available | Avoid |
What you get
A clearer decision before you buy
Score, valuation, market context, and ownership timing sit in one place so the next move is obvious.
How it helps
- Screen domains with value evidence, not just score decoration.
- Jump from market research to analysis without losing context.
- Move viable names into watchlist and acquisition planning.
Product Coverage
Everything needed to move from idea to acquisition
Acquisition logic
Decide whether a name is worth your time before you reach out.
Score, value, risk, registrar timing, and resale status stay in one view, so the call is grounded in evidence.
Comparison
Compare names side by side.
Run a head-to-head or a 3 to 5 domain battle and see which name leads on liquidity, brand strength, and acquisition fit.
Watchlist
Track domains like a pipeline.
Monitor expiry windows and value drift, and keep a target price and stance on every name you follow.
Market layer
Ground every estimate in reported sales.
TLD medians, category breakdowns, saved screens, and outlier flags keep the analysis tied to observed history.
Workflow
From sourcing a name to deciding whether it deserves budget
01
Source
Use the assistant or market page to surface names worth screening.
02
Analyze
Review the score breakdown, valuation evidence, and comparable sales.
03
Decide
Set a target price, a budget, and a buy, watch, or avoid call.
04
Monitor
Move the name to your watchlist when timing matters more than buying now.
Decision Model
Score
Brandability, TLD strength, and risk
Value
ML + comps + benchmark blend
Context
RDAP, resale posture, and market state
Action
Buy, watch, avoid, or monitor
Market Data Layer
TLD benchmarks, pricing anchors, and market posture at a glance
Tracked extension
.com
₹2.91L
Primary liquidity benchmark
Tracked extension
.ai
₹1.83L
Premium startup and AI demand
Tracked extension
.io
₹1.33L
Developer and product-led demand
Tracked extension
.in
₹2.24L
Country-sensitive pricing, buyer-fit dependent
Core Modules
The research layers behind the product
Comparable sales
Nearest reported sales by TLD, length, and category shape, each with a similarity score.
Value projection
A scenario range over time that shows upside and uncertainty without promising returns.
Investment report
A rule-based buy, watch, or avoid call alongside an AI-written explanation.
Market screens
Save reusable views, such as .ai startup names within a set price band.
Why it matters
One workspace, multiple decision lenses
Common Questions
The questions people ask first
How is this different from a registrar search?
A registrar tells you whether a name is free. This adds the parts that decide whether it is worth buying: comparable sales, a blended valuation, ownership history, and a watchlist to track it over time.
How is the value estimate produced?
It blends a trained ML model, the nearest reported sales, and TLD benchmarks, then applies risk-aware caps. Each figure is shown with the evidence behind it.
Is the data real?
Valuations use a local dataset of reported domain sales plus live RDAP lookups. The sample figures on this page are illustrative. Run a domain to see real output.
Get Started
Jump straight into the product
Start with a domain, move into market research, or use the assistant to source new ideas.