Atlas, Outcome pricing for AI-native companies
Atlas · Pricing, packaging, and outcome validation
Your buyers want to pay for outcomes.Your systems can only prove usage.
Stop introducing friction and risk into your deals. Let Atlas define the outcome, prove it happened, and price the contracts around it.
THE DELIVERABLE
Pricing model
Figma + Notion
Outcome spec
Signed by both sides
Pricing page
React component
Sales one-pager
Migration plan
Linear + doc
What we do
Designed, shipped, migrated, and then verified.
A senior pod and an agent layer rebuild your pricing. Strategy, meters, tiers, contracts, page copy, sales deck, billing spec, and the outcome definitions behind every charge.
AI-NATIVE COMPANIES WE SERVE
Who we serve
AI and SaaS companies where a pricing decision now moves eight figures.
Companies between $10M and $100M whose pricing was designed for a business one third their current size.
TWO WEEKS
Kickoff → Launch
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How fast
Two weeks to a decision. Then a managed migration.
You've already had the strategy deck. This is the part that ships, including the move of your existing book.
The outcome problem
Your buyer wants to pay for results. Your systems can only prove usage.
That gap is where outcome deals die in procurement. Atlas closes it.
01 · DEFINE
Name the outcome
Pick the one unit your buyer already budgets for: a meeting booked, a ticket resolved, a claim processed. Not a proxy for effort.
02 · MEASURE
Prove it in your data
Instrument the outcome, attribute it, and reconcile it against what customers actually experienced. If you can't measure it, you can't invoice it.
03 · DEFEND
Put it in the contract
Floors, caps, true-ups, and dispute language, so finance and procurement sign without renegotiating the model every quarter.
The team
Senior humans. Specialized agents. One pod.
Humans own judgment: packaging, narrative, the argument. Agents run the analysis underneath. You get the output of both.
No junior consultants learning on your data.
HumansAgents
HUMAN · LEAD
Michael Hoy
Principal Strategist
20 years pricing B2B SaaS and AI. 3x Founder, Ex-Pendo GTM VP. Runs every engagement from kickoff to handoff.
StrategyPackagingSales enablementNarrative
HUMAN
Laura Cruickshanks
Revenue Research Lead
Ex-Pendo and Salesforce. Conducts customer and segment research. Turns transcripts into quantified willingness-to-pay.
ResearchWTP modelingCustomer validation
HUMAN
Seimith Suth
Monetization Architect
Ex-Gusto, Podium, Y Combinator. Designs meter, tier, and contract structures. Formerly pricing at Figma and Airtable.
ImplementationUsage pricingContracts
AGENT
Izzy
Pricing Strategy Director
Proposes meters, tiers, and price points. Models 40+ scenarios per engagement and surfaces the three worth a human debate.
StrategyScenarios
AGENT
Kai
Data Engineer
Ingests usage, CRM, contracts, and win/loss data. Builds the queryable context graph every downstream decision runs on.
DataContext graph
AGENT
Bronte
Finance Engineer
Turns every pricing scenario into a revenue forecast your CFO will defend. Models churn and expansion, quantifies the cost of doing nothing.
ForecastingUnit economics
The real cost
Every month your pricing is wrong is ARR you'll never get back.
Pricing that fit you a year ago is bleeding revenue today. Our engagements average +38% ARR lift in year one. Every quarter you defer is margin you don't recover.
2wks
Kickoff to complete pricing package
+38%
Average ARR lift across engagements
1,200+
Companies in the Atlas pricing dataset
48hrs
Fastest seat → outcome model flip we've shipped
Trusted by AI & SaaS teams
Why the dataset matters
Any model can generate a pricing framework. Ours is trained on 10,000 that actually ran.
A model gives you a framework. Ours has seen what happened to conversion, churn, and expansion when 1,200 companies actually shipped.
Outcome pricing, proven ↓
ArchitectAI-nativeSeat → outcomes
+15%
conversion lift per pricing iteration
3 model iterations shipped
“Architect wanted to charge per meeting booked. Flipping the model took 48 hours. Proving the meeting was theirs was the harder half.
One that actually ran ↓
EGI · AlfredAI agentsCredit-based pricing
42% MoM
revenue growth after the credit model rebuild
3 model iterations · 4 months · 1 GTM unlock
“Atlas turned pricing from a bottleneck into our fastest growth lever. We ran three model iterations in four months, each lifted conversion 15%+, and the GTM team owns it end-to-end without an engineering ticket in sight.
Shikhar Mishra
Co-founder & CEO, Alfred.sh
Enterprise procurement ↓
ChargemateEV charging platformMercedes-Benz on the buy-side
“Atlas gave us the flexibility to balance predictability for buyers like Mercedes-Benz with real upside for us. Usage-based with custom minimums and maximums, plus the ROI frameworks our reps actually run. Pricing stopped being the bottleneck and became the wedge.
Bradford Crist
Co-founder & CEO, Chargemate
$250k
new revenue in 2 months after the packaging rebuild
$1M+ net new ARR tracking · enterprise wedge unlocked
Usage-based pricing Outcome-based contracts Outcome validation Attribution logic Dispute resolution AI token economics Packaging narrative Seat → usage migration Enterprise contracts Willingness-to-pay Meter design Usage-based pricing Outcome-based contracts Outcome validation Attribution logic Dispute resolution AI token economics Packaging narrative Seat → usage migration Enterprise contracts Willingness-to-pay Meter design
How it works
Two weeks. Three phases. One complete pricing package.
Every engagement follows the same arc, adapted to your data and your stage.
PHASE 01 · DAYS 1–4
Ingest & map
Agents ingest your product usage, CRM, contracts, and win/loss data. Humans run 5–7 customer interviews and build your pricing context graph.
→ Connect Segment / Amplitude
→ Import HubSpot contracts
→ 5 customer interviews
✓ Context graph: 412 nodes
PHASE 02 · DAYS 5–9
Model & design
Agents propose meters, tiers, and price points, simulated against your historical data. Humans pressure-test, refine, and write the packaging narrative.
→ 14 pricing scenarios
→ Revenue simulation (-12% to +41%)
→ 3 finalist models
✓ Recommended: usage + tier
PHASE 03 · DAYS 10–14
Package & migrate
Production-ready pricing page copy, sales deck, objection handlers, and billing implementation spec. Then we run the migration of your existing book.
→ Pricing page copy + HTML
→ Sales deck + enablement kit
→ Stripe / Metronome spec
✓ Migration plan live
Get started
Your buyers want outcomes. Make them provable.
We define the outcome, verify it happened, and price the contracts around it. A principal responds within one business day.