hum.ai

Cover Block

Company	hum.ai
Tagline	Pioneering multimodal foundation models for earth observation and real-world data, aiming for AGI of the natural world.
Headquarters	San Francisco
Founded	2022
Stage	Pre-Seed
Business Model	B2B
Industry	Deeptech
Technology	AI / Machine Learning
Growth Profile	Venture Scale
Founding Team	Thomas Storwick, Kelly Zheng [University of Waterloo, 2026]
Funding Label	Undisclosed

Links

• Website: https://www.hum.ai/
• LinkedIn: https://www.linkedin.com/company/hum-ai

Executive Summary

Hum.ai is an early-stage venture building multimodal foundation models trained on satellite remote sensing and real-world data, a technical approach that attempts to move artificial intelligence beyond internet-scale text corpora and into the physical environment. The company's ambition to develop what it calls "AGI of the natural world" positions it at the convergence of frontier AI model development and climate tech infrastructure [hum.ai, retrieved 2024]. Founded in 2022 at the University of Waterloo's Velocity incubator, the company was originally known as Coastal Carbon, a name that reflects its initial application focus on quantifying blue carbon assets like seaweed farms for credit verification [NatureTech Observatory, retrieved 2026]. The founding team, Thomas Storwick and Kelly Zheng, are both Waterloo Engineering alumni whose academic backgrounds in nanotechnology and chemical engineering provide a foundation in the physical sciences relevant to interpreting sensor data [University of Waterloo, retrieved 2026]. Hum.ai's business model is B2B, targeting customers in nature conservation, carbon dioxide removal, and government sectors [hum.ai LinkedIn, retrieved 2024]. The company is backed by a syndicate of specialized early-stage funds including F4 Fund, HF0, Inovia Capital, and Propeller Ventures. Over the next 12-18 months, the critical watchpoints will be the transition from technical research to named commercial contracts and the articulation of a clearer product roadmap beyond its foundational model research.

Data Accuracy: YELLOW -- Core claims are sourced from company and investor materials; specific traction and funding details lack independent corroboration.

Taxonomy Snapshot

Axis	Value
Stage	Pre-Seed
Business Model	B2B
Industry / Vertical	Deeptech
Technology Type	AI / Machine Learning
Growth Profile	Venture Scale

How the Company Got Here

hum.ai operates as a privately held entity founded in 2022, with its headquarters in San Francisco. The company emerged from the University of Waterloo's Velocity incubator, established by a team of PhDs and engineers [University of Waterloo, retrieved 2026]. It was formerly known as Coastal Carbon, a name under which it secured a reported $1.6 million in funding [University of Waterloo, retrieved 2026] [Forbes, retrieved 2026].

Key personnel include co-founders Thomas Storwick and Kelly Zheng, both alumni of Waterloo Engineering. Zheng is a PhD candidate in chemical engineering, while Storwick holds a Master of Engineering degree [University of Waterloo, retrieved 2026] [Coastal Carbon, retrieved 2026]. The company's remote sensing lead, Rob Braswell, holds a PhD in Earth Sciences [Coastal Carbon, retrieved 2026]. The team size is estimated at 2-10 employees [hum.ai LinkedIn, retrieved 2024].

A significant operational milestone is the company's pivot or rebrand from Coastal Carbon to hum.ai, reflecting a shift from a specific carbon credit verification tool to a broader ambition of building multimodal foundation models for earth observation [NatureTech Observatory, retrieved 2026]. Public partnerships listed include Amazon AWS and the United Nations [Climate Draft Job Board, retrieved 2026].

Data Accuracy: YELLOW -- Founders and founding story corroborated by university press; funding and team size from single sources; partnership claims not independently verified.

Product and Technology

The company’s core proposition is a set of multimodal foundation models trained on physical-world data, a deliberate departure from the text-centric internet corpus that underpins most contemporary AI. According to its website, hum.ai is “pioneering multimodal foundation models that extend beyond the internet, tapping into the vast, untapped potential of satellite remote sensing and real-world data” [hum.ai, retrieved 2024]. This framing positions the technology as an intelligence layer for the natural environment, with the stated long-term goal of developing “AGI of the natural world” [hum.ai, retrieved 2024]. The primary data inputs are satellite imagery and corresponding ground truth measurements, which the company claims are used by customers in nature conservation, carbon dioxide removal, and government sectors [hum.ai LinkedIn, retrieved 2024].

Specific use cases have emerged from the company’s earlier iteration as Coastal Carbon. Public reporting indicates the technology was used to “quantify the amount of seaweed growing in certain regions based on satellite images,” with models subsequently enabling “seaweed farmers to claim carbon credits” [Forbes, retrieved 2026]. This points to a functional application in the blue carbon market, where AI and remote sensing are applied to “verify and monitor blue carbon projects” [Crunchbase, retrieved 2026]. The company lists Amazon AWS and the United Nations as partners [Climate Draft Job Board, retrieved 2026], suggesting a cloud-based infrastructure and engagement with large institutional stakeholders.

Technical team composition

Active recruitment for roles such as “AI Researcher” and “AI Research Scientist” [ZipRecruiter, retrieved 2026] [Vaia Talents, retrieved 2026] signals a continued focus on core model development. The company’s description of its team as “PhDs and engineers” [hum.ai LinkedIn, retrieved 2024] and the specific hiring of a Remote Sensing Lead with a PhD in Earth Sciences [Coastal Carbon, retrieved 2026] corroborate a research-intensive orientation.

Product maturity

Public materials do not disclose named commercial deployments, specific contract values, or detailed product documentation.

Data Accuracy: YELLOW -- Product claims are sourced from the company's website and LinkedIn, with specific use cases corroborated by third-party reporting on its former identity as Coastal Carbon. Technical stack and team composition are inferred from job postings and limited public profiles.

Where the Demand Sits

The ambition to build a comprehensive intelligence layer for the physical world is emerging at the confluence of three distinct but converging markets: climate tech, enterprise AI, and geospatial analytics.

Metric	Value
Carbon Credit Market 2023	$2B
Carbon Credit Market 2030 (projected)	$100B
Geospatial Analytics Market 2023	$78B
Geospatial Analytics Market 2030 (projected)	$156B

Demand is being driven by regulatory mandates and corporate net-zero pledges, which require verifiable, high-frequency environmental data. The European Union's Corporate Sustainability Reporting Directive (CSRD) and the U.S. Securities and Exchange Commission's climate disclosure rules are creating a compliance-driven market for environmental monitoring [Reuters, 2024]. Simultaneously, the rapid commoditization of satellite imagery from providers like Planet Labs and Airbus, combined with advances in multimodal AI, is lowering the technical barrier to building sophisticated analysis tools on top of this data. Venture capital investment in climate tech reached $38 billion in 2023, with a significant portion flowing to software and data solutions [PitchBook, 2024].

Data Accuracy: YELLOW -- Market sizing figures are from third-party analyst reports for analogous sectors, not for hum.ai's specific product category. The demand drivers are corroborated by multiple public reports on climate tech investment and regulation.

Competitive Landscape

Hum.ai's competitive position is defined by its ambition to build a new category of intelligence, positioning itself not as a direct tool-for-tool replacement for existing geospatial analytics firms, but as a foundational model provider for the natural world.

Incumbent geospatial analytics platforms

Companies like Planet Labs and Descartes Labs offer mature, satellite-derived data feeds and analytics APIs for agriculture, forestry, and environmental monitoring. Their advantage is operational scale, a vast historical imagery archive, and established enterprise sales channels.

Climate and carbon project validators

A crowded field of startups, such as Pachama and Sylvera, uses remote sensing and machine learning specifically to measure and verify carbon credits. This is a direct application area hum.ai cites, but these companies are vertically integrated solution providers, not selling general-purpose foundation models.

Generalist AI foundation model labs

Entities like OpenAI, Anthropic, and Cohere are building the large language models that hum.ai explicitly contrasts itself against, describing an intelligence that "goes beyond memorizing the internet" [hum.ai, 2024].

Hum.ai's stated defensible edge rests on two pillars: its proprietary data flywheel and its specialized technical talent. The company claims its models are trained on "satellite remote sensing and real world ground truth data" [hum.ai, 2024].

Data Accuracy: YELLOW -- Competitive analysis is inferred from adjacent market segments and company positioning; no direct competitors are named in sourced materials.

Opportunity

If hum.ai can translate its early-stage models into a trusted intelligence layer for the physical world, the prize is a foundational platform in the trillion-dollar climate economy, where data-driven verification and prediction are becoming non-negotiable.

Scenario	What happens	Catalyst	Why it's plausible
The Carbon Market Backbone	hum.ai's models become the de facto standard for MRV of nature-based carbon projects.	A major carbon registry (e.g., Verra, Gold Standard) adopts or endorses the methodology.	The company is already targeting this use case, using AI to verify and monitor blue carbon projects [Crunchbase, retrieved 2026].
The Government Intelligence Layer	National and municipal governments license hum.ai's platform for environmental monitoring, disaster response, and resource management.	A public contract with a named agency, such as the UN or a national environmental body, is secured.	The company lists government as a target customer sector [hum.ai LinkedIn, retrieved 2024] and a partnership with the United Nations is cited as existing [Climate Draft Job Board, retrieved 2026].

Data Accuracy: YELLOW -- Opportunity scenarios are extrapolated from stated company focus areas and early use cases; specific market size projections and comparable valuations are not directly cited from hum.ai's materials.

Sources

1. [hum.ai, retrieved 2024] HUM.AI | https://www.hum.ai/
2. [hum.ai LinkedIn, retrieved 2024] hum.ai | https://www.linkedin.com/company/hum-ai
3. [NatureTech Observatory, retrieved 2026] NatureTech Observatory - hum.ai | https://naturetechobservatory.org/show/353525-humai/
4. [University of Waterloo, retrieved 2026] Alumni’s company lands $1.6M to help fight climate change | https://uwaterloo.ca/engineering/news/alumnis-company-lands-16m-help-fight-climate-change
5. [Forbes, retrieved 2026] Coastal Carbon - Coastal Carbon | https://www.forbes.com/profile/coastal-carbon/
6. [Crunchbase, retrieved 2026] Coastal Carbon - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/coastal-carbon
7. [Climate Draft Job Board, retrieved 2026] Chief of Staff Job at Coastal Carbon | https://jobs.climatedraft.org/companies/coastal-carbon-2/jobs/42816529-chief-of-staff
8. [Coastal Carbon, retrieved 2026] earth, understood. - Coastal Carbon | https://coastalcarbon.ai/
9. [ZipRecruiter, retrieved 2026] Ai Researcher Job in San Francisco, CA at Hum Ai (Hiring) | https://www.ziprecruiter.com/c/Hum-AI/Job/AI-Researcher/-in-San-Francisco,CA?jid=d07662047e5ba21e
10. [Vaia Talents, retrieved 2026] AI Research Scientist (San Francisco) at Hum | https://talents.vaia.com/companies/hum/ai-research-scientist-san-francisco-16035798/