EverestLabs.AI

Cover Block

PUBLIC

Name	EverestLabs.AI
Tagline	AI-powered vision systems, data platforms, and robotic sorting arms for recycling and materials recovery facilities. [EverestLabs, retrieved 2025]
Headquarters	Fremont, California [LinkedIn, retrieved 2025]
Founded	2018 [Crunchbase, retrieved 2025]
Stage	Seed [Crunchbase, retrieved 2025]
Business Model	Hardware + Software
Industry	Cleantech / Climatetech
Technology	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Solo Founder
Funding Label	Undisclosed
Total Disclosed Funding	$28.37M [CB Insights, retrieved 2026]

Links

PUBLIC

• Website: https://www.everestlabs.ai
• LinkedIn: https://www.linkedin.com/company/everestlabsai

Executive Summary

PUBLIC EverestLabs.AI is applying AI and robotics to a fundamental industrial bottleneck, targeting the recycling industry's persistent struggles with labor shortages and low material recovery rates. Founded in 2018 by Sami Selcuk, the company has built a full-stack automation platform, RecycleOS, which combines high-speed computer vision, robotic sorting arms, and a data analytics layer to identify and recover recyclables from mixed waste streams on existing conveyor lines [PRNewswire, May 2024]. The company's wedge is a focus on rapid deployment and lower capital expenditure compared to traditional optical sorters, aiming to deliver a payback period measured in months [Everestlabs, retrieved 2025].

Selcuk leads a team with seasoned VPs in engineering, product, and sales, bringing experience from robotics, industrial tech, and the waste sector itself [Everestlabs, retrieved 2025]. The company is venture-backed, with investors including Xplorer Capital, Translink Capital, and Benhamou Global Ventures, and has raised a total of $28.37 million across several rounds [CB Insights, retrieved 2026]. Its business model combines hardware sales or leases for its robotic systems with recurring software revenue from the RecycleOS data platform.

Over the next 12-18 months, the key watch points are the scalability of deployments beyond initial lighthouse customers like Veolia, the validation of claimed operational savings in public case studies, and the company's ability to translate its technical differentiation into durable commercial contracts in a conservative, capital-intensive industry. Data Accuracy: YELLOW -- Core company details and funding total are confirmed; specific round details and performance claims are partially corroborated or company-sourced.

Taxonomy Snapshot

Axis	Classification
Stage	Seed
Business Model	Hardware + Software
Industry / Vertical	Cleantech / Climatetech
Technology Type	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Solo Founder
Funding	Undisclosed

Company Overview

PUBLIC

EverestLabs was founded in 2018 by Sami Selcuk, who remains the company's CEO [EverestLabs, retrieved 2025]. The company is headquartered in Fremont, California, a location that places it within the broader San Francisco Bay Area's industrial and technology ecosystem [Crunchbase, retrieved 2025]. Selcuk's background, described by the company as involving prior experience in Silicon Valley companies and startups, suggests a founder motivated by applying advanced technology to a traditional industrial problem [EverestLabs, retrieved 2025].

Public milestones are anchored by customer deployments. In August 2023, CNBC reported on the company's technology, highlighting its robotic arms capable of up to 80 picks per minute and its AI models trained on millions of images [CNBC, Aug 2023]. A more significant public validation point came in May 2024, when waste management giant Veolia announced the deployment of EverestLabs' AI-powered recycling robotics at its Southwark facility in London, marking the startup's first international installation [PRNewswire, May 2024]. This followed earlier deployments with Veolia in North America, indicating a growing enterprise footprint.

The company's funding history, while not fully detailed in public announcements, shows consistent venture backing. Crunchbase records investment from firms including Xplorer Capital and Translink Capital [Crunchbase, retrieved 2025]. A more recent data point from CB Insights indicates a Series B round of $9.67 million led by Benhamou Global Ventures in March 2025, bringing total confirmed funding to $28.37 million [CB Insights, retrieved 2026].

Data Accuracy: YELLOW -- Foundational facts (founding, HQ, CEO) are confirmed by the company site and Crunchbase. Funding amounts are corroborated by CB Insights, but some round details remain incomplete. Customer milestones are cited in press releases.

Product and Technology

MIXED EverestLabs's core offering is a vertically integrated hardware and software system designed to retrofit existing recycling lines. The company's RecycleOS™ platform combines high-speed computer vision, robotic arms, and a data analytics suite, aiming to replace or augment manual sorting stations [PRNewswire, May 2024]. The system identifies and recovers specific recyclable materials,plastics, metals, fibers, paper, and cardboard,from mixed waste streams on conveyor belts, with robotic arms capable of executing up to 80 picks per minute [CNBC, Aug 2023] [EverestLabs, retrieved 2025]. This performance claim, if validated in operational settings, would represent a significant productivity gain over human sorters.

The technology's wedge is its focus on the complex, dirty environment of materials recovery facilities (MRFs). The AI vision models are trained on millions of images of recyclable materials to maintain accuracy despite variable lighting, occlusion, and contamination [CNBC, Aug 2023]. The accompanying software provides real-time data and analytics on material composition, throughput, and contamination rates, which the company markets under four solution categories: Robotic Sorting, Audit & Compliance, Line Optimization, and Plant Monitoring [EverestLabs, retrieved 2025]. The platform also offers customizable sustainability metrics, such as estimated greenhouse gas and CO2e savings [EverestLabs, retrieved 2025].

Deployment and integration appear to be a key part of the product proposition. Public messaging emphasizes rapid installation on existing conveyor lines without major facility overhauls, positioning it as a lower-capex alternative to large, centralized optical sorters [PRNewswire, May 2024]. The tech stack is inferred from job postings to include robotics control systems, computer vision pipelines, and cloud-based data platforms, though specific frameworks and infrastructure details are not publicly disclosed.

Data Accuracy: YELLOW -- Core product claims are confirmed by company materials and press releases. Performance metrics (80 picks/min) are cited in media but lack independent operational verification. Tech stack details are inferred.

Market Research

PUBLIC The market for AI and robotics in recycling is defined by a structural labor shortage and regulatory pressure to improve recovery rates, a combination that creates a clear economic case for automation.

Third-party sizing for this specific niche is not available, but analogous markets provide a sense of scale. The broader industrial robotics market is projected to reach $75.7 billion by 2028, according to a report cited by MarketsandMarkets [MarketsandMarkets]. The global waste management market, a key end-market for EverestLabs, was valued at $1.6 trillion in 2024 and is forecast to grow at a compound annual rate of 5.4% through 2032 [Grand View Research]. The company's serviceable addressable market (SAM) is a subset of this, targeting materials recovery facilities (MRFs) and plastics reclaimers in North America and Europe. The company's own materials suggest the wedge is replacing manual sorting stations, where labor costs and inefficiency are highest [PRNewswire, May 2024].

Demand is driven by several persistent tailwinds. Labor availability remains a chronic issue for MRFs, which are often located in industrial areas and involve repetitive, physically demanding work. EverestLabs cites the potential to reduce a facility's labor costs by 30-50% [EverestLabs, retrieved 2025]. Simultaneously, brand owner commitments and Extended Producer Responsibility (EPR) legislation are mandating higher recycled content in packaging, which in turn pressures recyclers to deliver higher-purity material streams. The company's data platform, which tracks material composition and contamination, directly addresses this need for verifiable quality [PRNewswire, May 2024].

Adjacent and substitute markets include traditional optical sorters and air jets, which represent a higher-capex, less flexible automation path, and manual labor, which remains the incumbent but is increasingly costly and scarce. EverestLabs positions its robotic cells as a modular alternative that can be deployed on existing lines without major retrofits, emphasizing lower capital expenditure [PRNewswire, May 2024]. The key regulatory forces are EPR laws, which are advancing in multiple U.S. states and in the EU, and municipal recycling targets that penalize contamination. These rules effectively mandate investment in sorting technology to meet compliance standards, creating a non-discretionary spend category for facility operators.

Given the absence of a specific market report for AI recycling robotics, the following table summarizes the cited sizing for adjacent sectors that define the opportunity perimeter.

Market Segment	2024 Size	Projected CAGR / 2032 Size	Source
Global Waste Management	$1.6 trillion	5.4% (CAGR to 2032)	[Grand View Research]

is that EverestLabs is operating at the intersection of two large, growing markets: waste management and industrial automation. While the precise TAM for its niche is unquantified in public research, the macro drivers,labor scarcity and regulatory mandates,are well-documented and provide a durable, multi-year tailwind for adoption.

Data Accuracy: YELLOW -- Market sizing is drawn from analogous, broad-sector reports; specific TAM for AI recycling robotics is not confirmed by a dedicated third-party study.

Competitive Landscape

MIXED EverestLabs competes in a specialized niche where AI and robotics are being applied to modernize a historically manual, low-margin industrial process.

Company	Positioning	Stage / Funding	Notable Differentiator	Source
EverestLabs.AI	AI vision + robotic arms + data platform for MRFs; emphasizes rapid deployment and lower capex.	Seed, Series A, Series B; $28.37M total raised (estimated).	Integrated RecycleOS data platform for analytics and compliance; targets retrofit on existing lines.	[CB Insights, retrieved 2026], [PRNewswire, May 2024]
AMP Robotics	Pioneer in AI-guided robotics for recycling; develops both hardware and the underlying AI platform.	Later stage; raised over $150M.	Extensive deployment footprint; vertically integrated from AI to robot manufacturing.	[Crunchbase, retrieved 2025]
Glacier	Develops AI-powered robots for sorting recyclables at a lower price point.	Early stage; raised $7.7M Seed.	Focus on affordability and ease of use for a broader range of facility sizes.	[Crunchbase, retrieved 2025]
ZenRobotics	Heavy-duty robotic waste sorting systems, originally from Finland, for construction & demolition waste.	Acquired by MHS Global in 2022.	Specialization in heavier, bulkier waste streams beyond post-consumer MRFs.	[Crunchbase, retrieved 2025]
Ishitva Robotic Systems	India-based developer of AI and robotics systems for sorting municipal solid waste.	Early stage.	Focus on waste management challenges and economics in emerging markets.	[Tracxn, retrieved 2026]
Greyparrot	AI waste analytics software; provides computer vision for waste audits but does not sell robotic arms.	Series A; raised $14.5M.	Pure-play software model analyzing waste composition for brands and regulators.	[Crunchbase, retrieved 2025]

The competitive map segments into three primary layers. First, integrated robotics providers like AMP Robotics and EverestLabs sell full hardware-software systems, competing directly on pick speed, accuracy, and total cost of ownership. Second, software-only analytics firms such as Greyparrot compete for the data intelligence portion of the budget, potentially as a precursor or complement to automation. Third, adjacent substitutes include traditional equipment manufacturers like Tomra and Bulk Handling Systems, which sell large, capital-intensive optical sorters and entire sorting lines. EverestLabs positions its robotic cells as a modular, lower-capex alternative to these large systems for specific sorting tasks [PRNewswire, May 2024].

EverestLabs's current edge appears to be its specific emphasis on the data layer and rapid retrofit. While competitors also offer data dashboards, EverestLabs markets RecycleOS as a central platform for audit, compliance, and line optimization, not just robot control. The claim of deployment on existing lines within weeks, versus the longer integration cycles for major optical sorter retrofits, is a tangible operational wedge. This edge is durable if the company continues to build proprietary datasets from its deployments that improve sorting algorithms and analytics. However, it is perishable if larger competitors with deeper R&D budgets replicate the software suite or if pure-play software vendors partner with robot OEMs to create equivalent bundled offerings.

The company's most significant exposure is to AMP Robotics's scale and vertical integration. AMP's larger funding base supports broader R&D and a more extensive installed base, which in turn generates more training data. Furthermore, AMP manufactures its own robots, potentially yielding cost advantages EverestLabs may not have as a systems integrator using third-party arms. EverestLabs is also exposed in the heavy-fraction sorting segment dominated by players like ZenRobotics, where its systems, optimized for post-consumer packaging on fast conveyors, may not be applicable.

The most plausible 18-month scenario hinges on adoption velocity in mid-tier MRFs. If EverestLabs can consistently demonstrate its promised four-month payback period and sign a series of regional waste operators beyond its flagship Veolia deployment, it will secure a defensible position as the agile, data-centric alternative. In this case, a winner would be a channel-focused competitor like Glacier, if its lower-cost model proves more attractive to smaller facilities. A loser would be the pure software analytics firms, if integrated providers like EverestLabs successfully bundle analytics for free with their hardware, making a standalone software sale harder to justify.

Data Accuracy: YELLOW -- Competitor profiles and funding are confirmed via Crunchbase and Tracxn; EverestLabs's differentiators are sourced from its PR. Direct, detailed performance comparisons between these private companies are not publicly available.

Opportunity

PUBLIC The prize for EverestLabs is a dominant position in the $1.2 trillion global waste management market by automating its most critical and expensive bottleneck: the manual sorting of recyclables.

The headline opportunity is to become the default AI and robotics operating system for materials recovery facilities (MRFs), a role analogous to what Rockwell Automation or Siemens is for discrete manufacturing. The evidence for this reachable outcome lies in the company's early wedge: its systems are designed for rapid deployment on existing conveyor lines with a lower capital expenditure than traditional optical sorters [PRNewswire, May 2024]. This practical focus on integration and payback period, claimed to be as little as four months [EverestLabs, retrieved 2025], directly addresses the capital constraints and operational conservatism of the waste industry. Winning the trust of a global operator like Veolia for deployments in both North America and the UK provides a critical proof point that the technology works at scale in complex, real-world environments [PRNewswire, May 2024].

Two plausible growth scenarios illustrate the paths from early traction to massive scale.

Scenario	What happens	Catalyst	Why it's plausible
Platform Standardization	RecycleOS becomes the mandated data and control layer for all automation within major waste management conglomerates.	A top-5 global waste firm (e.g., Waste Management, Republic Services) signs an enterprise-wide framework agreement for fleet-wide deployment.	Veolia's international rollout demonstrates the system's adaptability across regulatory regimes and facility layouts [PRNewswire, May 2024]. The push for ESG reporting creates demand for the platform's granular sustainability analytics [EverestLabs, retrieved 2025].
Vertical Integration into Commodity Trading	The data platform evolves from a facility optimization tool into a real-time feedstock intelligence service for plastics and metals buyers.	EverestLabs partners with a major commodity trader or packaging producer to provide certified material stream data, enabling premium pricing for recovered commodities.	The company already emphasizes data visibility across the recycling value chain, tracking material types, brands, and contamination rates [PRNewswire, May 2024]. This data has inherent value beyond the sorting process itself.

What compounding looks like is a classic data and distribution flywheel. Each new robotic installation in a facility generates millions of additional images of waste streams, which are used to further train and refine the AI vision models, improving pick accuracy and speed for all customers [CNBC, Aug 2023]. This creates a performance moat that becomes harder for new entrants to match. On the commercial side, a successful deployment with one site operator within a large waste management group lowers the sales friction for rolling out to sister facilities, creating a land-and-expand dynamic rooted in proven operational savings. The data platform, RecycleOS, adds a software layer that increases customer stickiness; once a facility's performance metrics and reporting are built on the platform, switching costs rise significantly.

The size of the win can be framed by looking at a public comparable. AMP Robotics, a direct competitor, has raised over $150 million in venture funding and is frequently cited as a category leader. While no public valuation is available, the scale of its financing suggests investor belief in a multi-billion dollar outcome for the right automation platform in recycling. If EverestLabs executes on the Platform Standardization scenario, capturing a meaningful share of the thousands of MRFs in North America and Europe, a valuation in the high hundreds of millions to low billions is a plausible outcome (scenario, not a forecast). The company's reported $28.37 million in total funding to date provides a runway to pursue these paths [CB Insights, retrieved 2026].

Data Accuracy: YELLOW -- Opportunity framing relies on company claims for value propositions and payback periods, which are unverified. Market context and competitive landscape are corroborated by public sources.

Sources

PUBLIC

1. [EverestLabs, retrieved 2025] EverestLabs - AI-Powered Recycling Robots | https://www.everestlabs.ai

2. [PRNewswire, May 2024] Veolia Adds EverestLabs' AI-Powered Recycling Robotics in First International Deployment | https://www.prnewswire.com/news-releases/veolia-adds-everestlabs-ai-powered-recycling-robotics-in-first-international-deployment-302541595.html

3. [CNBC, Aug 2023] EverestLabs using robotic arms and AI to make recycling more efficient | https://www.cnbc.com/2023/08/08/everestlabs-using-robotic-arms-and-ai-to-make-recycling-more-efficient.html

4. [Crunchbase, retrieved 2025] Everestlabs.AI - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/everestlabs-ai

5. [LinkedIn, retrieved 2025] Everestlabs.AI | LinkedIn | https://www.linkedin.com/company/everestlabsai

6. [CB Insights, retrieved 2026] EverestLabs - Products, Competitors, Financials, Employees, Headquarters Locations | https://www.cbinsights.com/company/everest-labs

7. [Tracxn, retrieved 2026] Everest Labs - 2026 Company Profile, Team, Funding & Competitors - Tracxn | https://tracxn.com/d/companies/everestlabs/__QXPbajtKDlLmEBz4dXhQ-_ZEPHNn6ym-RLP-vM1I98s

8. [MarketsandMarkets] Industrial Robotics Market | https://www.marketsandmarkets.com/Market-Reports/industrial-robotics-market-643.html

9. [Grand View Research] Waste Management Market Size, Share & Trends Analysis Report | https://www.grandviewresearch.com/industry-analysis/waste-management-market