RECOMMENDATION SHARE BY PROMPT DEPTHPILOT OBSERVATION
Established leaders Emerging SaaS
2026 PILOT EDITION • UPDATED AUG 22
AI RECOMMENDATION OBSERVATORYTHE ORACLE / FIELD PLATE 01
The Emerging
SaaS Index
The independent measure of which emerging software companies are breaking into AI recommendations, before they become category leaders.
BREAKOUT SIGNAL Smaller vendors displace incumbents most often in context-rich promptsMODEL GAP Only 31% of recommendations overlap across all six modelsNEW ENTRY 7 products entered new buying scenarios in this pilot
01Who is gaining
BREAKOUT RANKING
Who is gaining
recommendation share?
The Breakout Score combines recommendation growth, model expansion, buyer-scenario breadth and consistency. It is designed to find momentum, not reward company size.
#CompanyBreakout scoreAI share12 weeksCoverage
01TPreview dataset
Representative pilot data demonstrates the framework; it is not a final public ranking.
Read methodology02Context is where
THE BREAKOUT SIGNAL
Context is where
challengers win.
Generic prompts default to market leaders. Add a team, constraint, integration or budget and the recommendation graph opens up.
Specificity creates a discoverability surface that smaller SaaS companies can realistically own.
more emerging vendors surfaced in highly constrained prompts than generic category prompts.
Representative pilot signal03Not every market
CATEGORY INTELLIGENCE
Not every market
moves the same way.
We measure concentration and volatility separately. A fragmented category can still be stable; a concentrated one can change overnight.
MARKET MAP / PILOT18 CATEGORIES
Breakout velocityBubble size = recommendation breadth
OPEN FIELDFAST CONSOLIDATINGNICHE & STABLEINCUMBENT CONTROLLEDAI visibility71+11.2%Forms64+12.8%CRM48+9.4%Support52+7.1%Payroll29+2.6%Security34+3.1%
FRAGMENTED MARKETCONCENTRATED MARKET
04There is no single
MODEL DISAGREEMENT
There is no single
AI recommendation.
A company can lead in Claude and disappear in Gemini. The index preserves those differences instead of collapsing them into a deceptive average.
CROSS-MODEL OVERLAPTOP 5 RESULTS
31%shared recommendations
across all six models
across all six models
05One profile. Every
COMPANY INTELLIGENCE
One profile. Every
recommendation signal.
A practical view of where a product wins, which models carry it, and the third-party sources shaping its position.
EXAMPLE PROFILE / FORMS
Tally
Europe · Bootstrapped · tally.so
INDEX POSITION01↗ 4 places
View full profile BREAKOUT SCORE91.4↗ 18.2
AI RECOMMENDATION SHARE24.8%↗ 6.1 pts
BUYING SCENARIOS3812 newly entered
MODEL COVERAGE6/6Full coverage
01Forms for bootstrapped SaaS+18%
02Notion-native workflows+15%
03Unlimited responses on a budget+11%
04European privacy requirements+9%
06What rising SaaS
OBSERVED BREAKOUT PLAYBOOK
What rising SaaS
companies do differently.
The companies gaining recommendation share are not relying on a single tactic. They make their product legible to models, keep the evidence current, and earn independent mentions across the web.
01 ACCESS
Make your pages easily accessible to LLMs
Clear crawl paths, structured pages, descriptive markup and stable URLs give assistants fewer reasons to miss or misread the product.
02 FRESHNESS
NEWREPURPOSED+27%
Create fresh content, new and repurposed
Publish original findings, then turn strong ideas into focused pages, comparisons and updated explanations that match real buyer questions.
03 AUTHORITY
BRAND
MEDIACOMMUNITYREVIEWSPARTNERSDig into outreach and digital PR
Earn relevant third-party coverage, expert mentions and community citations. Independent sources often carry more recommendation influence than owned pages.
RESEARCH NOTE
These are recurring inputs observed around companies gaining recommendation breadth. They are practical levers, not a promise of placement in any model.
SHAREOF.AI / 202607Built to be inspected,
OPEN METHODOLOGY
Built to be inspected,
not merely believed.
Every public result will expose its sample, run date, prompt family and model coverage. Companies cannot pay to alter measured rankings.
Define the market
We map real buying jobs, company sizes, constraints, integrations and budgets.
Construct prompts
Each category uses generic, persona, workflow, constraint and comparison prompt families.
Run repeatedly
Prompts are sampled across six models and repeated to measure consistency, not one-off output.
Resolve entities
Aliases, product names and parent companies are normalized before recommendation share is calculated.
Score momentum
Growth, breadth, cross-model expansion and consistency combine into the Breakout Score.
Publish evidence
Public profiles show methodology, sample size, timestamps and representative answer excerpts.
RESEARCH INTEGRITY
Editorial rankings are independent. Sponsorships and enhanced profiles will always be labeled and will never change measured scores.
Research principlesEMERGING SAAS / 2026Find the recommendation surface your company can own.
FREE DISCOVERABILITY SCANSee where you enter
See where you enter
the AI buying journey.
We’ll map the buyer scenarios where you appear, the competitors already ahead, and the recommendation gaps that look reachable.