For post-PMF founders & C-levels

See where your GTM
leaks margin.

GTM economics, decoded. Get visibility into which segment × channel combinations your go-to-market is leaking margin - and unlock the better alternatives hiding in your own data.

Built from your operational data + your founder wisdom

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Map your move - start here

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Map the move Product-line × geo margin Demonstrate ROI to your customers Make it count Map the move Product-line × geo margin Demonstrate ROI to your customers Make it count
What we deliver

Real ICPs. ROI you can show your customers.
Allocation you can defend.

Three outcomes - each tied directly to the resource-allocation decisions you'll need to make before the next board meeting: which product lines, which geographies, which segments get the next dollar.

OUTCOME 01
Your real ICPs
Not the personas in your deck. The customers actually paying you, retaining, expanding, and carrying margin - segmented by what you can see and what you've learned operating.
OUTCOME 02
ROI you can demonstrate to your customers
The value your platform delivers per product-line, per geography, per cohort - quantified in terms your customers and your board both understand. Not blended. Mapped to how claims economics actually work.
OUTCOME 03
Your allocation framework
A working framework you own and operate. Survives board scrutiny. Tied to the decisions you actually make - not a deck you read once.
The whole story

Six pages. Read them all.

01 / WHAT WE DO
What we are. What we aren't.
A consultancy tailored to startup pace. Three outcomes. Specific deliverables.
Read
02 / WHO
Who we work with.
Post-PMF founders feeling the gap between data and decisions.
See fit
03 / WHY YOU NEED IT
It's beyond dashboards.
Why mid-level analysts and generic tools leave you with insights you can't act on.
The case
04 / HOW WE WIN TOGETHER
Six rules. Four phases.
The framework that fits a founder's pace, budget, and attention.
The framework
05 / CASES
Engagement patterns.
Four composite scenarios - pain, resolution, impact arcs from real engagements.
See cases
06 / ABOUT
Why we built this.
A practice built around one conviction about how startup founders actually scale.
The story
Two ways to start

Skim or sprint -
your call.

Book a call when you want to talk through the gap. Take the diagnostic when you want to see where it lives, in 3 minutes, before you call.

Book a call Take the diagnostic
01 / What we do

A data consultancy
tailored to how you actually move.

Most consultancies operate on enterprise time. Your business doesn't. AionScale is built around the constraints that actually govern a startup founder's life: pace, budget, and attention.

What we actually do.

AionScale is a data consultancy that turns your customer data and your founder wisdom into real ICPs and real department ROIs - the clarity you need to make confident allocation decisions toward your scale goals.

The deliverable isn't a dashboard. It's a working framework: outputs you can defend in board rooms, tied directly to how you'll spend the next dollar across customers, channels, teams, and bets.

Smarter decisions across all three growth motions.

We help founders and operators sharpen decisions across the three motions that compound - Acquire (marketing, sales), Build (product, data, R&D), and Retain (customer success) - by clarifying ICP fit, customer ROI, and team ROI in one connected picture.

01
Acquire - your real ICPs
Not the personas in your deck. The segments actually paying, retaining, expanding, and carrying margin - segmented by what your data shows and what you've learned operating.
02
Build & Retain - ROI you can show your customers
Per product-line, per geography, per cohort. Quantified value your platform delivers - defensible to your customers' CFOs and your own board. Mapped to how claims economics actually work.
03
Your allocation framework
A working framework you own and operate after we leave. Survives board scrutiny. Connects ICP clarity directly to the next-dollar decision: which product line, which geography, which segment gets the resources next.

Tailored to startup reality.

Three constraints define how we work:

A
Pace
Engagements measured in weeks, not quarters. Designed for founders who need confidence by the next board meeting - not the next fiscal year.
B
Budget
Sized for startup cash, not enterprise procurement. Scoped tightly so you know what you're buying, what it returns, and when.
C
Attention
We don't run six parallel workstreams. We require focused time from the founding team, in defined windows, with deliverables that justify the interruption.

What we walk away from.

Worth being explicit. AionScale is not:

  • A BI tool implementation or dashboard build-out - expensive and low-leverage without the underlying strategy.
  • A data engineering team or warehouse setup - months of cost burned before any insight reaches you.
  • A "fractional CDO" placeholder service - accountability-free headcount that protects nobody's P&L.
  • A research deliverable you read once and shelve - no follow-through, no operational impact.
  • An open-ended retainer nobody owns - scope drift, budget bloat, no clear ROI.
02 / Who it's for

If you're scaling on gut feel - read this.

Generic advisory promises generic results. We're explicit about who AionScale serves - and who we don't. If you don't see yourself below, save your time.

The founder we recognize.

You've reached PMF. Paying customers, a real GTM motion, ambitious scale targets ahead. You also have the gnawing sense that your dashboards aren't telling you what you need to know - and that scaling decisions are being made on signals you wouldn't fully defend.

"We're scaling but not sure where to double down. Our data is there, but the dashboards don't speak our domain."

Fit profile.

YES
Right fit
  • Your business stage: Reached traction - 5+ paying customers, enough to calculate real ICPs and granular ROIs
  • Your profile: B2B or B2B2C with complex unit economics - partner revenue, channel splits, or cohort dynamics that generic dashboards flatten into noise
  • Your ICPs: Mainly in the US or UK
  • Your TAM: Apparent opportunities across multiple markets, some already operational
  • Your Goal: Significant scale targets ahead
  • Your Buy vs. Build: Invest in core-business capabilities - use external solutions for the rest
  • Your board expectations: Modeled answers, continuous ROI & LTV clarity, reasoned allocation decisions
  • Your data ownership: No dedicated data leadership (CDO, VP Data, or equivalent). Ownership and business wisdom scattered across personas - considering a BI tool, first data hire, or similar advisory
  • Your allocation confidence: Medium to low -
    • Analysis tasks are sheets-based, ad-hoc efforts challenged by scale
    • Diverse sources with variable data quality and completeness
    • Data extraction and unification are extremely time-consuming
    • Economic models lack professional, domain-specific tuning
    • Resulting insights are lagging, partial, and debatable
    • Recommendations are partially backed by impact/cost assessments - frequently intuition-led
NO
Wrong fit
  • Your business stage: Pre-traction or fewer than 5 paying customers - not enough signal to model real ICPs and ROIs
  • Your profile: Pure SaaS or consumer products with standard unit economics, well-served by generic analytics solutions
  • Your ICPs: Primarily outside the US and UK
  • Your TAM: Single-market focus - not yet looking across geographies or verticals
  • Your Goal: Lifestyle, maintenance, or non-scale ambitions
  • Your Buy vs. Build: Building all data capabilities in-house, or fully outsourcing with no internal ownership intended
  • Your board expectations: Narrative-based reporting is sufficient - directional answers are acceptable
  • Your data ownership: Mature data leadership already in place (CDO, VP Data, or equivalent); or no internal ownership and no plans to develop it
  • Your allocation confidence: Already high - or not yet relevant; decisions are backed by strong, trusted analytics infrastructure
    • Reliable, scalable data pipelines already in production
    • Domain-specific benchmarks are tracked and trusted
    • Segment economics are visible and acted upon
    • Models are maintained by dedicated internal or embedded resources
    • Board receives modeled scenarios, not directional summaries
    • Resource allocation is data-driven and defensible

Three signals you'll recognize.

Two or more true? AionScale is built for your stage.

A
Board meetings end with "we'll model that"
When directional answers don't survive board scrutiny, you're feeling the gap between traction and confident scale. That gap is fundraise leverage.
B
Your dashboards don't speak your domain
Take rates, partner economics, cohort LTV by channel - if these aren't surfaced cleanly, you're benchmarking against generic SaaS metrics that don't match how your business actually makes money.
C
Allocation feels like a bet, not a call
If you can't predict the margin impact of doubling down on your best-performing geo, channel, or cohort, every scaling decision is hindsight measurement - not forward modeling.
03 / Why you need it

It's beyond dashboards.

Most founders don't have a data problem. They have a system problem. The tools, the people, and the plumbing all look reasonable on paper - and produce insights nobody trusts enough to act on.

The default startup data setup.

Most founders past PMF inherit some version of the same setup, by accident more than design:

01
A mid-level product analyst owns the dashboards
Smart, capable, often the most numerate person in the room - but stretched across product analytics, GTM reporting, board prep, and ad-hoc requests. Not a data leader. Not set up to be one.
02
Generic, poorly configured tools
Off-the-shelf BI, a CRM with default fields, a product analytics tool wired up in a sprint nine months ago. The defaults assume SaaS economics. Yours probably aren't pure SaaS.
03
Fragmented, inconsistent data
Customer records that don't reconcile across systems. Definitions that drift quietly. Partner data that arrives late, in different formats, and never gets cleaned. Each tool tells a slightly different version of the truth.
04
The output: insights you can't bet on
Dashboards that lag by weeks. Numbers that don't match between two reports. Partial views of customer behavior. You read them. You don't act on them. Because at the level of decision you're making, the confidence isn't there.

It's beyond dashboards.

The instinct, when something feels wrong, is to ask for another dashboard. A new chart. A different cut. That's treating the symptom.

The actual gap is upstream: you don't have a clear picture of who your real customers are, where each part of the business actually returns capital, and which signals are trustworthy enough to base allocation calls on. No dashboard fixes that. A framework does.

AionScale exists to close that gap before it costs you the next round.

What the gap actually costs.

It's rarely a single bad decision. It's a quarter spent doubling down on a channel that looks great on acquisition and bleeds on retention. It's the segment that quietly carries lower margin than the blended average. It's partner economics no one modeled before signing. None of these show up in a single dashboard alert.

They show up in the gap between projections and reality, six months later.

The conviction.

Most startup founders past PMF don't have a data problem. They have a system problem. They've inherited a stack - a mid-level analyst, a generic BI tool, a CRM with default fields, fragmented partner data - that produces dashboards nobody trusts enough to act on.

And critically: that stack ignores the most valuable input the founder has - their own operating wisdom. The patterns they see. The deals that felt off. The customers they knew were trouble before the data caught up. None of it makes it into the model.

Their data is fine. Their tools work. What's missing is a framework that exposes where margin actually leaks - and the operating wisdom to act on it.
04 / How we win together

Six rules.
Four phases.
No exceptions.

Our edge is a deliberate combination: deep analytics expertise, hard-won operator domain knowledge, and AI agents that amplify both. The result is a quality of insight and decision support a generalist consultant or a tool alone can't match. Knowing what good looks like - taste - is the differentiator.

The six rules.

RULE 01

Domain-first, not tool-first.

We start with your economics - take rates, cohort behavior, partner splits - before we touch a dashboard. Generic BI gets it backwards. It standardizes the surface and ignores the substance. Your domain is the substance.

RULE 02

Data + wisdom, not data alone.

Founder instinct is signal too. We bring your operating knowledge into the model - patterns you've seen, deals that felt off, customers you knew were trouble - and treat it as a source of evidence, not folklore.

RULE 03

Outcome-tied outputs.

Every analysis ties to a specific allocation decision. If it doesn't move a number on your P&L or change a cap allocation, we don't build it. Insight without decision is expensive curiosity.

RULE 04

Founder-grade clarity.

Outputs you can defend in board rooms - not dashboards your engineers maintain. If a non-technical founder can't explain it in two sentences, it isn't done. Sophistication is in the analysis, not the artifact.

RULE 05

Friction-path diagnosis.

We identify which of five scaling frictions is your actual constraint - ICP visibility, sales & pricing, marketing effectiveness, unified ROI, or data quality. Most founders treat the symptom they feel; we find the source. The visible pain is rarely the constraint.

RULE 06

Present founders. Reasoned every step.

We work directly with the founding team - not a delegate or liaison. Your operating knowledge and time are required inputs, not optional context. And every recommendation comes with its full logic and projected impact clearly stated. You should be able to interrogate anything we put in front of you - and we expect you to.

The friction-path model.

Where you feel scaling friction tells us where to look - but the visible pain is rarely the actual constraint. We diagnose across all five before we touch anything.

PATH 01
ICP visibility
Which customers actually make money. Segment-level, not blended.
PATH 02
Sales & pricing
Whether your pricing captures value - and where it leaks.
PATH 03
Marketing
Channel-level retention & CAC, not acquisition vanity.
PATH 04
Unified ROI
A single source of truth for allocation decisions.
PATH 05
Data quality
Whether your signals are trustworthy enough to bet on.

The four-phase engagement.

Each phase has a defined output and a clear exit criterion. Sized for startup pace, budget, and attention.

01

Diagnose

Friction-path identification and data foundation audit. Where's your actual constraint, and what data can we trust to address it?

≈ 2 WEEKS
02

Qualify

What data is reliable, what isn't, what's missing. We pair this with founder wisdom interviews to define the analytic surface - what we can model now vs. what needs instrumentation first.

≈ 1–2 WEEKS
03

Translate

Real ICPs and real department ROIs, mapped from your data and operating knowledge. Take rates, cohort LTV by channel, segment ROI, expansion scoring. The core build.

≈ 3–4 WEEKS
04

Allocate

Allocation framework handed back to the founding team. Survives board scrutiny. Owned by the operators. Designed to keep working as you scale.

≈ 1 WEEK

The method: analytics + domain + AI agents.

Analytics expertise. Years modeling unit economics, cohort behavior, channel margin, and claims patterns at the level where decisions actually move P&L.

Domain fluency. The "taste" that comes from operating inside these businesses - pattern recognition for what's signal, what's noise, what a number means before the chart loads.

AI agents that amplify, not replace. We use AI to compress weeks of data wrangling into hours, surface anomalies a human analyst would miss, and stress-test allocation hypotheses at speed. The best of all worlds: the velocity of AI with the judgment only real pattern recognition in this space provides.

What we don't do: build dashboards you'll inherit and abandon, run open-ended retainers, or generate decks no one references after the readout. The framework is designed to leave you with capability - not dependency.

05 / Use Cases

Use Cases - Engagement patterns

Pain → resolution → impact arcs representative of work we typically deliver. Identifying details obfuscated; specific clients are not named to protect engagement confidentiality.

Note These are composite cases, not single named clients.
Before you book

Questions founders
usually ask.

Everything you need to know before starting an engagement. If your question isn't here, book a call and ask us directly.

How long does an initial engagement take?
A first diagnostic takes 2–4 weeks. You’ll see a margin-leak read by product-line × geography, plus 2–3 prioritized alternatives - defensible enough to bring to your board.
What data do you need from us to start?
Read-only access to your claims/billing system, CRM, and product analytics is ideal - but we routinely start from exports. We tell you upfront which data is reliable enough to use and which isn’t.
What does it cost?
Fixed-fee for the initial diagnostic, scoped on the intro call based on data complexity and number of product lines. No retainers, no hourly billing on the first engagement.
How is this different from a BI tool or a generic consultancy?
BI tools standardize the surface and miss the substance - take rates, partner splits, cohort LTV by channel. Generic consultancies bring frameworks but not the domain fluency to know which numbers actually move decisions. We bring both, and we leave you with a model your team can run, not a deck.
How do you handle confidentiality?
NDA before any data access. Engagements are siloed; we don’t name clients publicly. Composite cases on this site are obfuscated for that reason.
Who will I actually be working with?
The founders, directly, on every engagement. No junior hand-offs. See the About page for backgrounds.
Ready?

Still have questions?
Let’s talk.

Book a 20-minute call. No pitch deck, no pressure. Just a conversation about your data and where the gaps might be.

Book a call Take the diagnostic
06 / About us

The practice behind
the framework.

What AionScale is.

AionScale is a specialized data consultancy built for post-PMF startups where scaling decisions outpace the data infrastructure supporting them. We work with founders who have real traction, real customers, and real complexity in their unit economics, but lack the analytical framework to allocate capital, prioritize segments, and defend those calls to a board.

AionScale is the bridge between traction and confident scale: a data consultancy that delivers real ICPs, real department ROIs, and a working allocation framework - in weeks, sized for the budget and attention startup founders actually have.

The founders.

T
Tamir Fridman
Co-founder · Data & Growth

16+ years building data and growth engines inside fast-scaling B2B SaaS - from early-stage startups to public market leaders. Senior analytics, product ops, and AI roles at Similarweb, ZoomInfo, and Spot.io (NetApp). Founder of PAI-TECH (acquired).

Track record includes enabling 2–3× company growth, building churn-prediction models with 84% accuracy, lifting product engagement by 50%, and shipping production AI systems. Currently runs Fridman Consulting - the data-advisory practice with paying customers that AionScale extends and scales.

Similarweb ZoomInfo Spot.io · NetApp PAI-TECH (exit) MBA · Ben-Gurion
LinkedIn
★ DRAFT - verify all companies, titles, and tenure dates before launch.
A
Arik Litvin
Co-founder · GTM & Practice

Product and growth executive with a decade operating B2B and B2B2C businesses at Payoneer, Similarweb, SAP, and Intango, among others. Brings the data-operations and GTM execution side of the practice, turning what founders already know into allocation decisions that hold up under scrutiny.

Moved the metrics that matter: ICP retention, NRR, and sales win rate. Owned end-to-end data analytics and vendor integrations across global orgs and markets.

Serial co-founder: built and exited from MVP to high profitable scale within 12 months. Tel Aviv-based, with a focus on Israeli-built ventures going to market in the US and UK.

Partners with Tamir on the full advisory chain, from raw customer data to board-defensible resource allocation.

Co-Founder Background ICP & Retention Uplift Sales Win-Rate Data-Ops Execution Agentic AI Tooling

Working with us.

Engagements are structured, time-boxed, and outcome-tied. We take on a small number of founder-led companies at any time - chosen for fit, not throughput. If you're feeling the gap between traction and confident scale, the cleanest first step is a conversation.

Two ways to start

Skim or sprint - your call.

Book a call when you want to talk through the gap. Take the diagnostic when you want to see where it lives, in 3 minutes, before you call.

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For founders past early traction

Pinpoint your biggest leakage concern.

You have bold scale targets. Smart resource allocation is non-negotiable - but how confident are your decisions, really?
Unlock your true allocation confidence score, based on your decision patterns, hidden blind-spots, and domain-specific benchmarks.

1
Select key challenge
Pick your decision area ICP, data trust, sales payback, channels, or team alignment - the one closest to your next call.
2
Answer questions
Show how you would decide today Across 4 real scenarios, pick the approach that matches how your team would actually decide.
3
End up with...
Your readiness score & gaps A 0–100 score across 7 dimensions, your weakest area named, and a concrete first check.
Confidence score across 7 decision areas · Your weakest area named and diagnosed · One concrete first check to act on today
Step 1

Where you are currently guessing the most?

Pick the area closest to your current decision. Your later answers shape the score.

Demo result
Score
0

Diagnosis

Main gap

Priority checks

Risk map

Risk 1
Risk 2
Next move
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