Atlas Freight Intelligence
Raise-Ready · Mar 14 2026Cleared all four lens thresholds — raise-ready, with one gap to close before you send.
Read from your deck as submitted. Every figure below is your own — quoted, not independently verified. This is what an investor sees on the page, not diligence.
On your own numbers, this reads as a raise-ready Seed deck — a coherent wedge, unit economics that hold up, and a moat that is starting to compound. One gap to close before you send: the US expansion thesis. You assert US demand but name no US customer, which leaves a capital-efficiency question a sharp investor will press in the first meeting.
The team you’re raising on
Direct founder–market fit on both sides of the problem — the buyer’s seat and the technical stack.
9Teamscore · /10
Akira Tanaka
Lived the exact buyer pain Atlas sells into — and the carrier-RFQ workflow it automates.
Priya Subramaniam
Shipped logistics rate-intelligence ML at scale before building Atlas’s.
State the US hire plan explicitly — role spec, timeline, budget. Seed investors funding US expansion want the hire plan as a deliverable, not an intent.
Is it growing — and can you prove the slope?
Healthy expansion signals — but the headline growth rate isn’t on a slide.
A Seed investor reads slope first. 130% NRR shows existing accounts grow — it does not show how fast you add new ARR. The deck states no month-over-month or quarter-over-quarter ARR growth rate and no time series. That single number is the one most likely to be asked for in the first five minutes.
How the deck scores, section by section
4 of 8 sections are investor-ready. Put your edits into the 4 that aren’t — Financials & Ask (7.0) first.
Financials & Ask
7.0The ask slide states $4M Seed with a 24-month runway and clear Series A milestones: $5M ARR, 8 US customers, NRR sustained above 125%. The use of funds is allocated across product (30%), sales (45%), and operations (25%).
The financial model summary shows three line items: revenue plan, headcount plan, and burn. The downside scenario is absent.
Add a downside scenario — the case where US sales ramp 40% slower than plan. One paragraph signals institutional maturity. The weakest section of an otherwise strong deck.
Business Model
8.0The pricing model is clearly stated: a SaaS subscription tiered by freight spend under management, plus a transaction-based fee on managed RFQs above a threshold. Unit economics are presented honestly, with the transaction fee compressing blended gross margin from 92% pure SaaS to 87% blended.
Unit economics slide shows LTV $187k against CAC $34k, payback 18 months, and a comparable named (Project44) for pricing logic context.
Add a pricing-tier evolution slide: the price increase taken in the last 12 months, the expansion ACV uplift from upsell, and the threshold where the transaction fee becomes the primary revenue driver.
Traction & Metrics
8.0Traction is specific, recent, and presented with directional honesty. The ARR slide shows $1.8M with monthly accrual visible. NRR at 130% is supported by a cohort retention chart spanning six quarters. The 32-customer count is broken out by geography, vertical, and ACV band. Maruyama Foods is named as the lighthouse account.
The cohort chart shows expansion from $42k initial ACV to $128k current ACV for the lighthouse customer. Three other named APAC customers are surfaced with anonymised ACV data.
Name one US customer here. The deck states "early US traction" but names none of the four US logos. At Seed, one named US customer with a quoted outcome is the difference between a US thesis and a US plan.
Go-to-Market
8.0GTM is structured around two channels: direct sales into mid-market shippers and a co-sell motion with two named APAC 3PLs. The CAC by channel is broken out. The direct channel shows a 4-month sales cycle with documented stage conversion; the co-sell channel shows shorter cycles and meaningful pipeline contribution.
GTM slide names the two 3PL co-sell partners and states the contractual terms (revenue share, exclusivity period). Pipeline coverage ratio is shown at 3.2x against next quarter’s number.
Replace the US channel placeholder with a specific entry plan — direct, partner-led, or both. Investors funding $4M will model US channel economics.
The analysis reads each slide, not just the deck
The full report reads all 14 main slides plus 6 appendix slides individually. Each read sits beside the slide it is reading.
Names CEO Akira Tanaka (ex-Yamato Holdings procurement, 11y) and CTO Priya Subramaniam (ex-Flexport ML platform), plus three hires with prior employers.
Founder-market fit is direct — both shipped procurement-relevant infrastructure at scale. The kind of team slide that earns a first meeting at Seed.
Add one operating metric per founder. "Designed Yamato's 2022 RFQ system that cut $4M in annual freight cost" converts a credential into evidence.
$1.8M ARR, 130% NRR, 32 customers. Lighthouse named (Maruyama Foods, 18 months, 3× ACV expansion $42k→$128k). Three APAC customers anonymised.
NRR is the standout — 130% means accounts expand faster than they churn. The 3× lighthouse expansion validates the procurement-automation thesis structurally.
This is where the Decision Brief’s “fix first” lands — name one US customer alongside the APAC names, right here.
$4M Seed, 24-month runway, three Series A milestones. Use of funds split 30/45/25 across product/sales/operations.
Sized for the milestones, sales-led allocation is correct for a Seed company with an established wedge. Milestones are specific, testable, stage-appropriate.
Add a downside scenario: "if US sales ramp 6 months late, runway extends to 28 months by deferring two hires." Signals institutional maturity.
What diligence will flag
Two dimensions sit at MEDIUM. None at HIGH or CRITICAL. Exit Risk does not apply at Seed and is not scored until Series B+.
Mechanism named and beginning to compound, but not yet quantified at scale — the data advantage's undisplaceable inflection point is unarticulated.
Healthy on the existing book; MEDIUM reflects unproven US sales productivity — the raise assumes US ACV and cycle comparable to APAC, unevidenced.
Defensibility findings
Three moat mechanisms named and supported. Project44 is enterprise tracking for Fortune 500 shippers; Atlas is mid-market rate intelligence — different ICP, wedge, and price point. Atlas is a category entry from below, not a feature against Project44.
Compounding rate-intelligence dataset
Each onboarding contributes proprietary priced-lane data. The dataset spans 84,000 priced routes, growing ~12,000/month, projecting 70% APAC mid-market coverage by Q3 2027. It cannot be replicated without comparable customer volume — a structural advantage that compounds with each procurement event.
Integration switching cost
Average onboarding is 6.5 weeks of ERP/TMS/carrier-API integration. Once live, customers reach 92% workflow dependency across procurement, finance, and ops. 130% NRR is partly a function of this depth — switching means reversing 6.5 weeks of work plus retraining three teams.
Asymmetric APAC distribution
Exclusive 24-month co-sell agreements with two of the top three APAC 3PLs contribute ~38% of new-logo pipeline. The exclusivity and relational nature create a regional distribution barrier a US-headquartered competitor would take 18–24 months to replicate.
Can the team ship the plan
One dimension at MEDIUM. None at HIGH or CRITICAL.
Two of 47 carrier integrations route ~41% of volume; mitigation planned but redundancy not yet executed.
Who Atlas can send this deck to today
Institutional Seed funds with B2B SaaS or vertical-tech theses — especially those building APAC operating presence.
On the deck’s own numbers, Atlas clears every Seed threshold: unit economics that hold up, a named lighthouse with expansion, a moat with a quantified mechanism, coherent use of funds, and a credible Series A path. The deck supports a 60-minute first meeting and a four-week diligence cycle.
Series A funds.
ARR is $1.8M against a $4–6M Series A bar. The US thesis is asserted but not evidenced through named customers. The moat is named but its compounding velocity is not yet quantified to the standard Series A funds require. Close one US customer, reach $3M+ ARR with named US logos, and quantify the dataset compounding rate to open those conversations.
Four next steps, ranked by impact
The Seed thesis funds US expansion, but the deck names no US logo. Investors surface this in the first meeting. One named US customer with a quoted outcome converts the expansion thesis from a plan to executed traction and moves Capital Efficiency from MEDIUM toward LOW.
VaultMoat sits at 71 because the mechanism is named but not quantified. A slide showing dataset growth velocity, per-customer contribution, and the coverage inflection point moves VaultMoat toward 80 and reframes "we have proprietary data" as "this advantage gets structurally harder to displace each quarter."
The two APAC 3PL partnerships are mentioned but their contribution and terms are not in the main deck. Surfacing the 38% pipeline contribution and the 24-month exclusivity moves GTM from credible to evidenced and reduces Capital Efficiency risk.
Investors will model 40% US sales slippage themselves. Pre-empting it — even one paragraph — lifts Financials & Ask from 7 to 8 and signals institutional maturity. The single highest-leverage one-slide addition Atlas can make.
The questions this deck invites — walk in ready
Every flagged gap becomes a question across the table. For each: a one-line way to answer, the proof to have open, and the artifact to send in follow-up.
Your traction is APAC. What is your evidence that US shippers convert at a comparable ACV and sales cycle?
Name the single closest US opportunity and its stage, and state the ACV and cycle-length assumption explicitly rather than implying parity with APAC.
The US pipeline by stage, plus one named US logo — even a pilot — with a target close date.
US channel-economics model (CAC, cycle, ACV by channel).
Project44 is well-funded. Why can it not simply add rate intelligence and displace you?
Lead with the ICP, wedge, and price-point difference — Atlas is a category entry from below, not a feature against an enterprise incumbent.
The dataset compounding rate (84k routes, +12k/mo) and the 92% workflow-dependency switching cost.
The moat-velocity slide showing the coverage inflection point.
Blended gross margin compresses to 87% with the transaction fee. Where does pricing power go at scale?
Name the threshold at which the transaction fee becomes the primary revenue driver, and the price increase already taken in the last 12 months.
Expansion ACV uplift from upsell and the pricing-tier evolution.
The pricing model tab / assumptions summary.
Scored against the Seed-stage rubric. The analysis reads only what is in your deck — it cannot verify your metrics, see your data room, or judge anything you did not put on a slide. Treat scores as how an investor will read the deck, not as diligence.
Run your own deck through the four lenses.
Same rubric, your numbers — VaultScore, the four-lens breakdown, and a ranked, slide-targeted action plan.
