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Polli Labs

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uuid02ls42k

Namestring
Polli Labs
Legal namestring
Polli Labs
Websiteurl
polli.ai
Company typeenum
Private
Founded yearint
2023
Descriptiontext

Polli Labs is a private, early-stage software company founded in 2023 and headquartered in Asheville, United States, with 1-10 employees. It develops AI software that converts raw field and camera-trap footage into taxonomy-aware ecological and wildlife insights, targeting research labs, conservation organizations, and educators/citizen science programs.

Its product is an open-source-first pollination analytics platform composed of three modular components — Linnaeus (taxonomy-aware computer vision with abstention and lineage-first training), Typus (taxonomy and geometry services supporting SQLite for offline and Postgres for production), and Cosmos (media-as-sample ingest with provenance tracking) — plus a core Polli Explorer demo gallery for visualizing validated detections, tracks, and exportable evidence with full lineage from raw footage to final identification. The stack is designed to be self-hostable on cloud, on-prem, or embedded environments.

The business model is product-led and freemium: the core platform ships as open-source packages on GitHub with a self-serve Explorer Demo for evaluation, while revenue generation is expected to come from enterprise support, custom integrations, and managed services routed through a single founder contact email ([email protected]). No pricing is publicly disclosed, no funding rounds or revenue figures are reported, and no institutional investors or named customers appear in the available data.

Short descriptiontext

Polli Labs builds open-source AI software that converts field camera footage into validated, provenance-tracked ecological and pollinator insights for research labs, conservation organizations, and educators.

Operating statusenum
Operating
Ownership categoryenum
Headcount rangeband
1–10
akta.pro rankint
HeadquartersAsheville, United States
HQ citystring
Asheville
HQ countrystring
United States
HQ regionstring
North America
Markets served

Serves global market

Keyword5 values
ecological AI software, pollinator monitoring analytics, wildlife computer vision, taxonomy-aware detection, camera trap video analysis
Industry2 codes
PRIMARYBPAEAHAG
Generative AI & LLM Solutions Services (RAG, Agents, Copilots)
Business & Public Services/IT & Digital Services (Managed Services, Systems Integration)/Data, Analytics & AI Services
SECONDARYAFAAAFAH
Drone/UAV Data Capture & Processing Software
Agriculture & Food Production/Agricultural Equipment & Technology/Precision Agriculture & Farm Management Software (GIS, IoT, Telematics)
NAICS code1 code
  • Surveying and Mapping (except Geophysical) Services54137
SIC code1 code
  • Services-Computer Integrated Systems Design7373
Product category
Ecological AI Analytics Software
Social media profiles2 records
GTM motion1 record

Each record includes

Type, Description, Source

Revenue model1 record
1Open Source Platform
TypeFreemium
Description

Core platform ships as open-source packages. Revenue model not explicitly disclosed - appears to monetize through enterprise support, custom integrations, or hosted services for organizations needing managed solutions.

polli.ai
Marketing channels4 records

Each record includes

Title, Type, Stage, Description, Source

Distribution channels2 records

Each record includes

Title, Type, Scope, Target buyer, Description, Source

Cost components5 values
Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales
GTM typeB2B
B2B
Offering typeSoftware
Software
Brand1 of 4 records shown
1Linnaeus
Description

Taxonomy-aware vision with abstention and lineage-first training.

polli.ai
+3 more records
Core offering1 text field

Polli Labs develops AI software that converts raw field camera and camera trap footage into taxonomy-aware ecological and wildlife insights. The platform stitches detection, taxonomy, and provenance into a single pipeline, composed of three open-source modules — Linnaeus (taxonomy-aware vision), Typus (taxonomy and geometry services), and Cosmos (media-as-sample ingest with provenance) — along with the Polli Explorer gallery demo for visualizing and exporting validated observations.

Differentiator
Functional benefit
Problem solved
Product overview1 text field

Polli is a unified pollination analytics platform that stitches detection, taxonomy, and provenance into a single pipeline. The platform consists of a core product (Polli Explorer) for visualizing and managing ecological observations, augmented by three open-source modular components: Linnaeus (taxonomy-aware computer vision with abstention), Typus (taxonomy and geometry services with SQLite/PostgreSQL support), and Cosmos (media-as-sample ingest with provenance tracking). Together these components enable labs, parks, and schools to process field camera footage from detection through taxonomy classification to exportable evidence with full lineage.

Product and service4 records
1Polli Explorer
CategoryCore Analytics Platform
Description

Interactive gallery and demo platform that visualizes validated ecological detections, observation timelines, and exportable evidence with provenance. Built for research labs, conservation organizations, and educators studying pollinators.

2Linnaeus
CategoryAI Vision Module
Description

Open-source taxonomy-aware computer vision module with abstention capability and lineage-first training. Processes visual inputs to identify species while knowing when to abstain from uncertain classifications.

3Typus
CategoryData Services Module
Description

Open-source taxonomy and geometry services module supporting SQLite for offline deployments and PostgreSQL for production environments. Handles taxonomic data management and spatial/geometric analysis.

4Cosmos
CategoryData Ingest Module
Description

Open-source media-as-sample ingest module that captures raw footage as data samples with full provenance tracking, ensuring today's footage can be used to answer tomorrow's research questions.

Scale indicator1 record

Each record includes

Type, Value, Description, Source

Recent move1 record

Each record includes

Date, Type, Title, Description, Source

Expansion highlight4 records

Each record includes

Type, Description

Peers10 records
1TrapTagger
TypeDirect peer
Description

AI-assisted platform for camera-trap image annotation and species identification. Directly comparable in automating taxonomy workflows on field camera data, with overlapping target customers in research and conservation.

2iNaturalist
TypeBroad incumbent
Description

Citizen science platform with AI-assisted species identification across all taxa. Comparable as an AI-enabled taxonomy tool for ecological observation, though broader in scope and serving a much larger, non-specialist audience.

3Arbimon
TypeDirect peer
Description

Rainforest Connection's platform for acoustic and biodiversity monitoring with AI-driven species detection. Comparable in providing AI-powered ecological monitoring infrastructure for researchers and conservation organizations.

4EarthRanger
TypeBroad incumbent
Description

Vulcan-funded conservation technology platform for protected area management. Comparable as infrastructure used by conservation organizations managing ecological monitoring programs, though more focused on operations and ranger data than CV-based taxonomy.

5Wildlife Insights
TypeDirect peer
Description

Google-supported platform that applies AI to camera-trap imagery for wildlife monitoring. Directly comparable to Polli in turning field camera footage into ecological insights, though broader across taxa rather than pollinator-specific.

6Rainforest Connection
TypeEmerging player
Description

Uses acoustic monitoring and AI to detect illegal logging and biodiversity in real time. Comparable as an AI-for-conservation player with a strong open-source/community ethos and overlapping target customers.

7eBird (Cornell Lab of Ornithology)
TypeBroad incumbent
Description

Massive citizen-science biodiversity database with AI-assisted tools. Comparable as infrastructure for ecological observation and taxonomy at scale, though focused on bird sightings and without Polli's CV-on-camera-footage pipeline.

8Conservation AI
TypeDirect peer
Description

AI platform applying machine learning to ecological monitoring data including camera traps and acoustic sensors. Comparable in using AI to convert raw field data into validated ecological insights for conservation organizations.

9MegaDetector (Microsoft AI for Earth)
TypeDirect peer
Description

Open-source computer-vision model for detecting animals, people, and vehicles in camera-trap images. Comparable as a CV pipeline for ecological field footage, though focused on detection rather than taxonomic classification with abstention.

10DeepForest
TypeDirect peer
Description

Open-source python package for tree and wildlife detection in aerial and ground imagery using deep learning. Comparable as an open-source CV tool for ecological monitoring with similar developer-led adoption patterns.

Market position
Strengths4 records

Each record includes

Headline, Details, Source

Weaknesses4 records

Each record includes

Headline, Details, Source

Competitive moat3 records

Each record includes

Type, Details

Key risks5 records

Each record includes

Headline, Details, Source

Key highlights6 records

Each record includes

Headline, Details, Source

Customer concentration

Classification, Details

Segment3 records

Each record includes

Title, Type, Primary, Description, Pain point addressed, Use case, Source

Ideal customer profile3 records

Each record includes

Profile, Firmographic size, Sales motion, Sales cycle length, Buying structure, Purchase trigger, Buyer persona, Geography, Industry vertical, Primary use case, Description, Pain points, Evidence proof points, Target buyer

Technology focused
Yes
API detail
Has APIbool
No

Docs URL, Description

AI capability4 records

Each record includes

Type, Description, Source

AI maturity
App detail

Has app

Feature4 records

Each record includes

Title, Differentiator, Description, Source

Core technology
Revenue estimate
Valuation estimate
Number of profiles
Profiles1 record

Each record includes

Name, Designation, Designation category, Overview, Profile commentary, Source

No data
No data
Funding overview

Funding stage, Last funding date, Total funding USD

Funding rounds

Each record includes

Round, Amount USD, Date, Pre money valuation, Total investors, Investors, News

Investors

Each record includes

Name, Type, Date of entry, Rounds participated, Website

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Each record includes

Name, Acquisition type, Announced date, Completed date, Status, Website, News

Investment

Each record includes

Name, Round, Announced date, Lead investor, Website, News

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Polli Labs

Ecological AI Analytics Softwarepolli.ai

Polli Labs builds open-source AI software that converts field camera footage into validated, provenance-tracked ecological and pollinator insights for research labs, conservation organizations, and educators.

What Polli Labs does

Polli Labs is a private, early-stage software company founded in 2023 and headquartered in Asheville, United States, with 1-10 employees. It develops AI software that converts raw field and camera-trap footage into taxonomy-aware ecological and wildlife insights, targeting research labs, conservation organizations, and educators/citizen science programs.

Its product is an open-source-first pollination analytics platform composed of three modular components — Linnaeus (taxonomy-aware computer vision with abstention and lineage-first training), Typus (taxonomy and geometry services supporting SQLite for offline and Postgres for production), and Cosmos (media-as-sample ingest with provenance tracking) — plus a core Polli Explorer demo gallery for visualizing validated detections, tracks, and exportable evidence with full lineage from raw footage to final identification. The stack is designed to be self-hostable on cloud, on-prem, or embedded environments.

The business model is product-led and freemium: the core platform ships as open-source packages on GitHub with a self-serve Explorer Demo for evaluation, while revenue generation is expected to come from enterprise support, custom integrations, and managed services routed through a single founder contact email ([email protected]). No pricing is publicly disclosed, no funding rounds or revenue figures are reported, and no institutional investors or named customers appear in the available data.

Polli Labs firmographics

Firmographics
Name
Polli Labs
Legal name
Polli Labs
Website
https://polli.ai
Company type
Private
Founded year
2023
Operating status
Operating
Headcount range
1–10 employees
Short description
Polli Labs builds open-source AI software that converts field camera footage into validated, provenance-tracked ecological and pollinator insights for research labs, conservation organizations, and educators.
Ownership category
akta.pro rank

Polli Labs industry classification

Industry
Product category
Ecological AI Analytics Software
NAICS
Surveying and Mapping (except Geophysical) Services (54137)
SIC
Services-Computer Integrated Systems Design (7373)
akta.pro industry
PRIMARYBPAEAHAG
Generative AI & LLM Solutions Services (RAG, Agents, Copilots)
Business & Public Services/IT & Digital Services (Managed Services, Systems Integration)/Data, Analytics & AI Services
SECONDARYAFAAAFAH
Drone/UAV Data Capture & Processing Software
Agriculture & Food Production/Agricultural Equipment & Technology/Precision Agriculture & Farm Management Software (GIS, IoT, Telematics)

Keywords

  • Ecological AI software
  • Pollinator monitoring analytics
  • Wildlife computer vision
  • Taxonomy-aware detection
  • Camera trap video analysis

Where Polli Labs is headquartered

Location

Headquarters

HQ city
Asheville
HQ country
United States
HQ region
North America

Markets served

Polli Labs business model

Business model
GTM type
B2B
Offering type
Software
Cost components
Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales

Revenue model

  1. Open Source Platform: Core platform ships as open-source packages. Revenue model not explicitly disclosed - appears to monetize through enterprise support, custom integrations, or hosted services for organizations needing managed solutions.

Go-to-market motion1 record

Distribution channels2 records

Marketing channels4 records

Polli Labs product offering

Product offering

Core offering

Polli Labs develops AI software that converts raw field camera and camera trap footage into taxonomy-aware ecological and wildlife insights. The platform stitches detection, taxonomy, and provenance into a single pipeline, composed of three open-source modules — Linnaeus (taxonomy-aware vision), Typus (taxonomy and geometry services), and Cosmos (media-as-sample ingest with provenance) — along with the Polli Explorer gallery demo for visualizing and exporting validated observations.

Product overview

Polli is a unified pollination analytics platform that stitches detection, taxonomy, and provenance into a single pipeline. The platform consists of a core product (Polli Explorer) for visualizing and managing ecological observations, augmented by three open-source modular components: Linnaeus (taxonomy-aware computer vision with abstention), Typus (taxonomy and geometry services with SQLite/PostgreSQL support), and Cosmos (media-as-sample ingest with provenance tracking). Together these components enable labs, parks, and schools to process field camera footage from detection through taxonomy classification to exportable evidence with full lineage.

Differentiator

Problem solved

Functional benefit

Brands

  • Linnaeus: Taxonomy-aware vision with abstention and lineage-first training.
  • Typus
  • Cosmos
  • Polli Explorer

Products and services

  • Polli Explorer Interactive gallery and demo platform that visualizes validated ecological detections, observation timelines, and exportable evidence with provenance. Built for research labs, conservation organizations, and educators studying pollinators.
  • Linnaeus Open-source taxonomy-aware computer vision module with abstention capability and lineage-first training. Processes visual inputs to identify species while knowing when to abstain from uncertain classifications.
  • Typus Open-source taxonomy and geometry services module supporting SQLite for offline deployments and PostgreSQL for production environments. Handles taxonomic data management and spatial/geometric analysis.
  • Cosmos Open-source media-as-sample ingest module that captures raw footage as data samples with full provenance tracking, ensuring today's footage can be used to answer tomorrow's research questions.

Companies that use Polli Labs

Customer profile

Segments3 records

Ideal customer profiles3 records

Polli Labs technology and API

Technology

Technology focussed Yes

API detail

Has API
No
API docs
API detail

Core technology

AI maturity

App detail

AI capability4 records

Feature4 records

Polli Labs partnerships and signals

Strategic signal

Scale indicators1 record

Recent moves1 record

Expansion highlights4 records

Polli Labs competitors and assessment

Company assessment

Direct peers

  • TrapTagger: AI-assisted platform for camera-trap image annotation and species identification. Directly comparable in automating taxonomy workflows on field camera data, with overlapping target customers in research and conservation.
  • Arbimon: Rainforest Connection's platform for acoustic and biodiversity monitoring with AI-driven species detection. Comparable in providing AI-powered ecological monitoring infrastructure for researchers and conservation organizations.
  • Wildlife Insights: Google-supported platform that applies AI to camera-trap imagery for wildlife monitoring. Directly comparable to Polli in turning field camera footage into ecological insights, though broader across taxa rather than pollinator-specific.
  • Conservation AI: AI platform applying machine learning to ecological monitoring data including camera traps and acoustic sensors. Comparable in using AI to convert raw field data into validated ecological insights for conservation organizations.
  • MegaDetector (Microsoft AI for Earth): Open-source computer-vision model for detecting animals, people, and vehicles in camera-trap images. Comparable as a CV pipeline for ecological field footage, though focused on detection rather than taxonomic classification with abstention.
  • DeepForest: Open-source python package for tree and wildlife detection in aerial and ground imagery using deep learning. Comparable as an open-source CV tool for ecological monitoring with similar developer-led adoption patterns.

Broad incumbents

  • iNaturalist: Citizen science platform with AI-assisted species identification across all taxa. Comparable as an AI-enabled taxonomy tool for ecological observation, though broader in scope and serving a much larger, non-specialist audience.
  • EarthRanger: Vulcan-funded conservation technology platform for protected area management. Comparable as infrastructure used by conservation organizations managing ecological monitoring programs, though more focused on operations and ranger data than CV-based taxonomy.
  • eBird (Cornell Lab of Ornithology): Massive citizen-science biodiversity database with AI-assisted tools. Comparable as infrastructure for ecological observation and taxonomy at scale, though focused on bird sightings and without Polli's CV-on-camera-footage pipeline.

Emerging players

  • Rainforest Connection: Uses acoustic monitoring and AI to detect illegal logging and biodiversity in real time. Comparable as an AI-for-conservation player with a strong open-source/community ethos and overlapping target customers.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat3 records

Key risks5 records

Key highlights6 records

Customer concentration

Polli Labs social profiles

Digital presence

Polli Labs financial estimates

Financial estimate

Revenue estimate

Valuation estimate

Polli Labs leadership team

Management profile

Number of profiles

Profiles1 record

Polli Labs funding detail

Funding detail

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

Polli Labs M&A and investment

M&A and investment

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Polli Labs

What does Polli Labs do?

Polli Labs develops AI software that converts raw field camera and camera trap footage into taxonomy-aware ecological and wildlife insights. The platform stitches detection, taxonomy, and provenance into a single pipeline, composed of three open-source modules — Linnaeus (taxonomy-aware vision), Typus (taxonomy and geometry services), and Cosmos (media-as-sample ingest with provenance) — along with the Polli Explorer gallery demo for visualizing and exporting validated observations.

Is Polli Labs a public or private company?

Polli Labs is a private company. It is classified as founder individual operated bootstrapped and is currently operating.

When was Polli Labs founded?

Polli Labs was founded in 2023. It employs 1 to 10 people.

Where is Polli Labs based?

Polli Labs is headquartered in Asheville, United States, in the North America region.

How does Polli Labs make money?

One revenue line is on record: open Source Platform.

Who are Polli Labs's main competitors?

Direct peers on record are TrapTagger, Arbimon, Wildlife Insights, Conservation AI, MegaDetector (Microsoft AI for Earth) and DeepForest. Broad incumbents are iNaturalist, EarthRanger and eBird (Cornell Lab of Ornithology). Rainforest Connection is listed as an emerging player.

Does Polli Labs have an API?

No public API is recorded for Polli Labs.

What industry is Polli Labs in?

Polli Labs's product category is Ecological AI Analytics Software. Its primary akta.pro industry code is BPAEAHAG, Generative AI & LLM Solutions Services (RAG, Agents, Copilots), with a secondary code of AFAAAFAH, Drone/UAV Data Capture & Processing Software. Its NAICS code is 54137 and its SIC code is 7373.

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