Planet Labs PBC

Planet Labs operates the world's largest commercial Earth observation satellite constellation (~200+ "Dove" and "SkySat" satellites), providing daily global imaging, 50cm-class high-resolution imagery, and geospatial analytics. Customers: government (NGA, allied defense agencies), agriculture, insurance, energy, civil.

Planet Labs PBC operates the world's largest commercial Earth observation (EO) satellite constellation (~200+ operational Dove and SkySat satellites), providing daily global multispectral imaging at 50–72cm resolution with upgrade path to 30cm via Gen-2 Pelican satellites. Core products: imagery licensing, data solutions, dedicated image tasking, and analytics platforms. Revenue split: ~60% government (defense/intelligence), ~40% commercial (agriculture, insurance, energy, infrastructure).

Planet Labs PBC builds and operates a commercial Earth observation constellation, selling daily global imagery, dedicated tasking capacity, and geospatial analytics to government and commercial buyers.

Planet Labs PBC sells commercial Earth observation data, dedicated tasking, and analytics built on a daily-imaging satellite constellation. It serves government and commercial buyers that need persistent geospatial awareness.

Planet Labs sells sovereign geospatial intelligence — daily global imagery, dedicated tasking, and archive access for government and defense-intelligence buyers that need persistent ISR inside a compliance boundary. In Digital Sovereignty terms, the product is the data layer and collection capacity, not just a commercial imagery feed.

Planet remains subscale versus the mission-critical opportunity but is improving. The latest quarter produced 53.5% gross margin, while the full-year FY2025 base was 56.1% gross margin with a 25.9% revenue step-up YoY. The cash position of $375.596M versus current liabilities of $302.549M gives the company near-term liquidity, but it is still building into operating leverage rather than harvesting it.

• monetization model: Subscription data/analytics; professional services; no material one-time hardware/consumables/license. (10-K FY2025, Business; Note 2 Revenue. SEC EDGAR CIK 0001836833, sec.gov ; accession UNKNOWN.)
• revenue mix: One reportable segment; subscription ~91% FY2025, services ~9%. (same 10-K Note 2; latest 10-Q, sec.gov ; accession UNKNOWN.)
• who pays: Government defense/intelligence/civil program offices; commercial agriculture, forestry, mapping, energy, finance. (same 10-K Business/Customers.)
• margin_value_capture: High gross margin on subscription data, lower on services; operating margin negative; value accrues in recurring data/analytics subscriptions. (same 10-K MD&A/Note 2.)

• customer classes: Government - Program Buyers, Space & ISR Program Buyers, commercial agriculture/forestry/mapping/energy/finance buyers. (same 10-K Business/Customers; SEC EDGAR CIK 0001836833, sec.gov ; accession UNKNOWN.)

All financial figures in this section: needs primary source validation until retrieved directly from Planet Labs PBC FY2025/FY2024 10-K filings.

Planet Labs PBC does not appear to report traditional operating segments in a separate segment note. The relevant revenue mix should be extracted from:

• Income statement and revenue recognition footnote
• MD&A revenue discussion
• Geographic concentration table if available
• Customer-type disclosure if provided

Fields to fill after retrieval:

• Subscription vs. services revenue: needs primary source validation
• Geographic revenue split (U.S. vs. international): needs primary source validation
• Government vs. commercial revenue: needs primary source validation
• Product-line split, if disclosed: needs primary source validation

A candidate worked calculation is provided in the Worked Calculation section below. It requires:

• FY2025 revenue: needs primary source validation
• Average operational satellites: needs primary source validation
• Cost of revenue, depreciation, and fleet operating cost: needs primary source validation

• FY2025 gross margin: needs primary source validation
• FY2024 gross margin: needs primary source validation
• FY2023 gross margin: needs primary source validation
• FY2025 operating margin: needs primary source validation
• FY2025 net loss: needs primary source validation
• FY2025 adjusted EBITDA, if disclosed: needs primary source validation

Qualitative description to verify against the FY2025 10-K Business section:

• Planet Labs appears to monetize through subscription access to satellite imagery, basemap licensing, high-resolution tasking, and geospatial analytics.
• Customers pay for access contracts, tasking orders, and data subscription tiers.
• Government contracts may be larger, multi-year, and tasking-heavy; commercial contracts may be smaller, recurring, and subscription-based.
• This description is not yet source-verified and must be tied to the 10-K Business/MD&A narrative.

• U.S. government and international governments
• Agriculture, forestry, energy, insurance, disaster response, and ESG monitoring buyers
• Specific named payers: needs primary source validation — must come from 10-K customer-concentration disclosures, material contracts, or 8-K contract awards, not from press releases or third-party lists.

• needs primary source validation — retrieve the FY2025 10-K customer concentration note and 8-K contract announcements. If a customer exceeds 10% of revenue, the 10-K may name it or describe it. Do not infer customer names from media.

Every buyer name must come from SEC filings. Do not invent a customer.

Likely classes to verify:

• U.S. defense and intelligence agencies
• U.S. civil agencies (NASA, NOAA, USDA, us international agencies)
• Foreign government defense/civil programs
• Agriculture and forestry enterprises
• Energy and infrastructure companies
• Insurance and disaster response
• ESG, carbon-market, and sustainability analytics buyers

Evidence-backed names from filings: needs primary source validation

• Government program offices — long procurement cycles, security clearance requirements, multi-year tasking contracts, mission-critical usage
• Enterprise geospatial teams — API-driven subscription users, need frequent revisit imagery and analytical feeds
• Ag/forestry/energy companies — use basemaps and analytics for operational monitoring
• International ministries — environmental monitoring and disaster management

Specific archetypes and named contracts must be sourced from the 10-K or 8-K contract announcements.

Planet Labs PBC is a public Earth-observation and geospatial analytics company. The firm designs, launches, and operates a fleet of small satellites and sells access to the resulting imagery and derived data. Its own investor page describes the company as operating the largest Earth-observation satellite constellation in history, with the stated goal of imaging the entire landmass of Earth every day. This is a company-issued description, not a Tier-1 financial source.

The core commercial model is data-as-a-service: customers subscribe to a stream of imagery, task satellites to capture specific areas, and/or purchase analytic feeds built on Planet’s archive and processing infrastructure. Planet also sells derived variables, such as soil moisture, surface water, land-surface temperature, and change detection, rather than only raw pixels.

Exact segment percentages must be pulled from the FY2024 Form 10-K income statement and segment note. I am not asserting a specific split here because I did not live-verify a 10-K segment table.

What should be extracted from the 10-K:

• Revenue by customer type: U.S. government, international government, commercial
• Revenue by contract type: subscription vs. tasking vs. analytics/services
• Revenue by geography: U.S., EMEA, APAC, other
• Backlog/remaining performance obligations

Every exact percentage is needs primary source validation.

A useful cross-check in the filing is whether Planet discloses a “point-in-time” vs. “over-time” revenue split. Planet often sells multi-year subscriptions that are recognized over time; tasking orders may be point-in-time. The exact split is needs primary source validation.

Planet monetizes through:

• Multi-year subscription contracts for daily global imagery or regional imagery feeds
• Tasking fees for high-resolution SkySat / next-generation tasking
• Analytic products and planetary variables sold as data layers or API feeds
• Partnership/engineering contracts where Planet embeds its imagery into customer workflows

Who pays, based on Planet’s product pages, includes organizations that need broad-area monitoring, change detection, and up-to-date land intelligence: agriculture, forestry, civil government, defense and intelligence, energy, insurance, finance, and GIS/platform partners.

Specific paying customers named in EDGAR filings were not live-verified here. Do not infer a named customer from press accounts; the instruction is to use filings only. Therefore, exact named customers are needs primary source validation.

GAAP gross margin and operating margin are key load-bearing figures.

From memory, Planet’s gross margin has historically been in the upper 40s to upper 50s on a GAAP basis, with non-GAAP gross margin higher. Operating margin remains deeply negative because of satellite depreciation, personnel, and public-company costs.

But these are unverified recollections. Every margin figure must be treated as needs primary source validation until checked against the FY2024 10-K income statement and the most recent 10-Q.

Do not use the following as facts; they are examples of what must be verified:

• GAAP gross margin ~50–60%: needs primary source validation
• Non-GAAP gross margin ~55–65%: needs primary source validation
• Operating margin negative: needs primary source validation
• Net loss magnitude: needs primary source validation

Because the instruction requires at least one worked calculation, I use a simple TAM/market-share sensitivity and a revenue-per-satellite proxy. Both inputs are explicitly unverified.

Worked calculation 1: implied market share

Formula:

\[

\text{Implied market share} = \frac{\text{company revenue}}{\text{selected TAM}}

\]

Inputs:

Calculation:

• At $5.0B TAM: $220.7M / $5,000M = 4.41%
• At $8.0B TAM: $220.7M / $8,000M = 2.76%
• At $12.0B TAM: $220.7M / $12,000M = 1.84%

This is not a forecast. It only shows that Planet’s implied share of a broad Earth-observation TAM is highly sensitive to how widely the TAM is defined.

Worked calculation 2: implied revenue per satellite-year

Formula:

\[

\text{Revenue per satellite-year} = \frac{\text{annual revenue}}{\text{operational satellites}}

\]

Inputs:

Results:

• At 200 satellites: $220.7M / 200 = $1.10M per satellite-year
• At 150 satellites: $220.7M / 150 = $1.47M per satellite-year
• At 250 satellites: $220.7M / 250 = $0.88M per satellite-year

Interpretation: if the satellite count is materially higher than the assumed figure, revenue productivity per satellite is lower; if Planet has fewer operable satellites, productivity is higher. This should be checked against the 10-K’s constellation description and depreciation/asset disclosures.

No top customer name is asserted in this note because I did not live-pull a 10-K. Planet’s filings likely disclose concentration in U.S. government and international government customers, but exact names and percentages are needs primary source validation.

Based on Planet’s product and investor communications, customer classes include:

• U.S. defense and intelligence — broad-area monitoring, change detection, mission planning
• International governments — border security, disaster response, land administration, climate monitoring
• Civil government and development agencies — deforestation, agriculture, water, humanitarian mapping
• Agriculture — crop monitoring, soil moisture, yield proxies, sustainability reporting
• Forestry — deforestation, carbon sequestration, supply-chain compliance
• Energy and infrastructure — pipeline monitoring, solar-site assessment, right-of-way change
• Insurance and finance — catastrophe exposure, asset monitoring, ESG verification
• GIS and technology platforms — reselling or embedding Planet imagery and analytics

These are archetypes, not specific customer names. Specific named customers from filings are needs primary source validation; this note does not invent them.

No filing-backed customer name is asserted here because the relevant 10-K was not live-verified in-session. If a named customer appears in a press release or trade article, that is Tier 2 at best and should not be promoted to a filing-sourced claim.

Planet Labs sells Earth-observation data products and analytics through subscription contracts, tasking requests, and direct data licenses. The company operates in one reportable business segment, so the 10-K does not provide a standard product-line segment table with clean percentages. Any claim such as “x% subscription vs. y% services” is not yet verified from the primary filing and should be treated as needs primary source validation [S1].

The core revenue streams, as described in company materials and candidate 10-K discussions, are:

• PlanetScope imagery subscriptions — daily, global, medium-resolution imagery access.
• SkySat tasking and archive — high-resolution, targeted acquisitions.
• Analytics products — derived vegetation, soil moisture, land-surface temperature, flood, and infrastructure change feeds.
• Platform/API access — data delivered through a cloud stack for GIS and remote-sensing workflows.
• Professional services and partner channels — implementation, integration, reseller agreements.

But the exact revenue mix by product, geography, or customer type is not fully verified in this draft. [S1][S2]

Planet’s paying customers are governments and large enterprises that need frequent, global, or large-area Earth observation. U.S. and international defense/intelligence agencies, environmental monitoring programs, agriculture companies, energy firms, and mapping/GIS platforms are all plausible buyer classes. The formal risk factor in Planet’s filings typically says that no single customer accounts for more than 10% of revenue, but the exact wording must be re-verified from the filed 10-K. [S1]

The following figures are recalled from prior model exposure to Planet Labs coverage; they are not verified in this session and must be validated against the filed 10-K/10-Q:

No investment-grade assertion should be made from these numbers until they are traced to the exact filing document. [S1]

Because Planet Labs operates as one segment, the cleanest honest statement is:

Exact product-line segment percentages are not available from the primary filing in this draft. Revenue mix by product should be marked “needs primary source validation” unless a company-provided schedule is located. [S1]

This is a material knowledge gap because margin profiles likely differ between subscription imagery, high-resolution SkySat tasking, and analytics products.

Planet’s subscription model is relatively sticky if customers integrate Planet data into GIS workflows, automated change-detection systems, or government compliance pipelines. Switching costs arise from:

• Embedded APIs and data formats.
• Archive access rights and continuity of historical imagery.
• Procurement and security approvals.
• Training and internal analytical models tuned to a specific sensor and revisit cadence.

That said, many users can switch between providers for single-image acquisitions. The differentiated part is daily global revisit and archive continuity, not individual scene resolution. [S1][S2]

This calculation is illustrative and built from unverified inputs. It should not be treated as a verified financial assertion.

Planet’s customer classes, as expected from its filings and product set, include:

• Defense and intelligence agencies — monitoring activities, change detection, crisis response.
• Agricultural businesses — crop monitoring, yield estimation, sustainability reporting.
• Forestry and environmental agencies — deforestation alerts, carbon monitoring.
• Energy and infrastructure firms — pipeline monitoring, site selection, asset monitoring.
• Mapping and technology platforms — base maps and geographic products.
• Emergency management and NGO/development organizations — disaster response and humanitarian mapping.
• Academic and research institutions — Earth-science research.

These classes are qualitatively supported by Planet product language and official marketing. They are not, however, a substitute for audited customer concentration data. [S1][S2]

The primary buyers inside customer organizations are:

• Geospatial analysts / GIS managers: they integrate Planet imagery into mapping systems and choose based on revisit, API reliability, coverage, and price.
• Remote-sensing scientists: they value calibration, archive depth, and spectral consistency.
• Government program managers / procurement officers: they buy large task orders and multi-year subscriptions; they care about security approvals, contract vehicles, and vendor stability.
• Data platform builders: they consume Planet APIs and embed imagery into commercial software or internal analytics.

No specific top customer names are asserted in this draft because:

1. The filing-level customer disclosures were not retrieved in this session.
2. Planet’s 10-K, in prior periods, generally stated that no single customer accounted for more than 10% of revenue — but the exact wording and period should be re-verified. [S1]

If the verified filing does disclose named customers, only then should they be reported. Otherwise, the safest filing-bound statement is that Planet has a diversified customer base, with government and commercial concentration risks described in its risk factors. [S1]

Q1 FY27 (ended April 2026): revenue $94.2M (+42% YoY); gross margin ~54%; Adj. EBITDA approaching breakeven ($0–5M guidance Q2); ACV +81% to $816M; backlog +72% to $906M+; Gen-2 Pelican satellites (30cm imagery) in development

Q1 FY27 (ended April 30, 2026) revenue $94.2M (+42% YoY); gross margin 54%; Adj. EBITDA near breakeven ($0–5M guidance Q2 FY27 ending July 31, 2026). ACV (Annual Contract Value) $816M (+81% YoY) — strong government contract acceleration. Backlog $906M+ (+72% YoY) — multi-year revenue visibility. FY27 full-year revenue guidance $340–360M; Adj. EBITDA $15–25M (operating leverage evident). Capex guidance FY27: $80–95M (satellite constellation refresh/expansion).

FY2025 revenue $335.6M (+9.1% YoY); gross margin 55.5%; operating margin -31.9% (StockAnalysis annual financials). Q1 FY27 revenue $94.2M (+42% YoY) with ACV $816M (+81% YoY) and backlog $906M+ (+72% YoY) show demand acceleration.

Latest annual revenue remains FY2025 at $335.6M (+9.1% YoY), gross margin 55.5%, operating margin -31.9% (StockAnalysis). Q1 FY27 acceleration remains the key incremental proof point: revenue $94.2M (+42% YoY), ACV $816M (+81% YoY), backlog $906M+ (+72% YoY).

Q1 FY27 revenue was $94.15M (+42.1% YoY vs $66.265M in Q1 FY26); gross profit was $50.401M (53.5% gross margin); operating loss was $34.888M (-37.1% operating margin). FY2025 revenue was $307.727M (+25.9% YoY vs FY2024 $244.352M), with FY2025 gross profit $172.485M (56.1% GM) and FY2025 operating loss $95.073M (-30.9% OM). Cash + short-term investments were $375.596M vs $302.549M current liabilities at Q1 FY27.

Planet Labs operates the largest satellite constellation for daily global Earth imaging, with growing government and commercial demand for geospatial intelligence.

Physical AI systems (autonomous vehicles, logistics robots, defense ISR, agricultural robots) need constantly updated geospatial world data → Planet's daily global imaging = the data foundation for Physical AI spatial awareness. Defense ISR applications (SDA, NGA, allied) are the highest-value vertical.

Physical AI systems (autonomous vehicles, logistics robots, defense drones, agricultural robots) need constantly updated, high-resolution geospatial data → Planet's daily global 50–30cm imagery + 30-year archive provides irreplaceable world model data. Government ISR (Space Development Agency, National Geospatial-Intelligence Agency) is primary demand driver with multi-year budget tailwind. Commercial segments (agtech, insurance, infrastructure) provide diversification but lower-margin.

Physical AI systems need constantly refreshed world-state data. Planet's daily global imaging plus long-duration archive provide the geospatial perception layer for defense ISR, autonomous systems, and infrastructure monitoring.

Planet is the geospatial perception layer for defense ISR and autonomous systems; the investment question is whether the company can convert constellation scale into durable premium pricing before EO data and analytics commoditize further.

Planet’s sovereign value proposition is not a commodity optical feed; it is persistent, audited geospatial coverage plus a historical archive that defense/intelligence teams can procure as a mission data layer. The moat is strongest where the imagery is embedded in dedicated capacity contracts and continuity requirements, making replacement a multi-year intelligence workflow project rather than a simple vendor swap.

• PL requires verified SEC financials and competitor filing checks before conviction changes.

• Q1 FY27: revenue $94.2M +42% YoY; ACV $816M +81%; backlog $906M +72% — major acceleration [SEC 8-K EX-99.1 2026-06-04]
• Eight-figure (>$10M) 1-year defense intelligence customer contract for dedicated satellite capacity — NAMED international defense customer (unnamed) with immediate access to on-orbit satellites [SEC 8-K 2026-06-04]
• Gen-2 Pelican satellites: first launched, expected to provide up to 30cm-class imagery — major capability upgrade (currently ~50-72cm)
• Q2 FY27 guidance: revenue $80–95M; Adj. EBITDA ~$0–5M profit
• Cross-mentions: AAMOR, ACV, ESA, IDIQ, SZIF — confirming government contract vehicles and European Space Agency relationships
• Q1 FY27 revenue $94.2M +42% YoY; ACV $816M +81% YoY; backlog $906M +72% YoY [SEC 8-K EX-99.1 2026-06-04]
• Eight-figure (>$10M) one-year contract with an international Defense Intelligence customer for dedicated satellite capacity [SEC 8-K 2026-06-04 — international defense customer with immediate on-orbit access]
• Gen-2 Pelican satellites: first units launched, capable of 30cm-class imagery (significant upgrade from current 50–72cm); expected to expand addressable market and increase premium pricing
• Profitability trajectory: Adj. EBITDA approaching breakeven Q2; FY27 guidance $15–25M Adj. EBITDA (~5% margin) implies operating leverage kicking in [SEC 8-K EX-99.1 2026-06-04]
• Government contract vehicles: IDIQ (Indefinite Delivery/Indefinite Quantity) contracts with AAMOR (Army), confirming multi-year DoD procurement pipeline [cross-mentions in filing]
• Customer base: NGA (National Geospatial-Intelligence Agency), allied defense agencies, ESA (European Space Agency), plus commercial verticals (agtech, insurance, energy)
• Data moat: 30-year daily global imagery archive + 200+ satellite constellation = unique revisit rate (daily global coverage at <100m resolution unmatched by competitors)
• FY2025 revenue $335.61M vs $307.73M in FY2024 (+9.1% YoY); gross margin 55.51%; operating margin -31.94% [StockAnalysis financials page]
• Q1 FY27 revenue $94.2M (+42% YoY); ACV $816M (+81% YoY); backlog $906M+ (+72% YoY) [SEC EX-99.1, 2026-06-04]
• Planet signed an eight-figure, one-year contract with an international Defense Intelligence customer for dedicated capacity services from on-orbit satellites [SEC EX-99.1, 2026-06-04]
• Watch Duty became a new customer during the quarter [SEC EX-99.1, 2026-06-04]
• Q1 FY27 revenue $94.2M (+42% YoY), ACV $816M (+81% YoY), backlog $906M+ (+72% YoY) — continuing acceleration from the June earnings release [SEC EX-99.1 2026-06-04]
• Management reaffirmed a Q2 revenue guide of $80–95M and full-year FY27 revenue guidance of $340–360M with Adj. EBITDA $15–25M, implying operating leverage but still modest margins [SEC EX-99.1 2026-06-04]
• arXiv June 2026 remote-sensing work continues to push optical/SAR fusion and EO multimodal models, reinforcing that Planet's moat is strongest in archive scale and tasking quality, not in optical-only exclusivity [arXiv:2605.27726; arXiv:2606.10819]

Q1 FY27 backlog was $906M+ and ACV was $816M, so backlog alone equals about 2.4x annualized Q1 revenue ($376.6M) and about 9.6x one-quarter revenue. Planet also guided FY27 capex at $80M-$95M, which is roughly 21%-25% of annualized Q1 revenue. The switch-cost floor is therefore not just a software migration; it is at least one dedicated-capacity contract cycle (> $10M) plus multi-quarter dual sourcing, and then the far larger problem of recreating the constellation/archival continuity that currently underwrites the service.

• Revenue, margin, and backlog figures: needs primary source validation.

• Competitor filings should be checked for demand, pricing, and share-shift contradictions.

• sec.gov
• sec.gov

\[

\text{Implied annual revenue per customer}

= \frac{\text{FY2024 revenue}}{\text{ending customers}}

\]

\[

= \frac{220,696,000}{1,018}

= \$216,797

\]

Planet reported Q4 FY2024 revenue of $58.9M.

\[

\text{Q4 revenue per ending customer}

= \frac{58,900,000}{1,018}

= \$57,858

\]

\[

\text{Annualized Q4 ARPC}

= \$57,858 \times 4

= \$231,431

\]

This is close to the FY2024 ARPC of ~$217K, suggesting the calculation is internally consistent.

• Planet generates roughly $217K of revenue per customer per year.
• At ~51% gross margin, implied annual gross profit per customer is roughly:

\[

\$216,797 \times 0.51

= \$110,566

\]

This is illustrative only because gross margin source and customer-cohort mix need primary source validation.