Arbel.ai

Cover Block

PUBLIC

Name	Arbel.ai
Tagline	AI-powered construction intelligence platform for real-time visibility into large-scale infrastructure projects. [BuiltWorlds, 2025]
Headquarters	Binyamina-Giv'at Ada, Israel [Join.com, 2026]
Founded	2025 [BuiltWorlds, 2025]
Stage	Pre-Seed
Business Model	SaaS
Industry	Proptech
Technology	AI / Machine Learning
Geography	Middle East / North Africa
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding Label	Seed
Total Disclosed	~$3,000,000 [StartupHub.ai, 2025]

Links

PUBLIC

• Website: https://www.arbel.ai
• LinkedIn: https://il.linkedin.com/company/arbelai
• Join.com (Careers): https://join.com/companies/arbelai

Executive Summary

PUBLIC Arbel.ai is a newly formed Israeli startup applying conversational AI to drone-captured imagery, aiming to give owners and engineering, procurement, and construction (EPC) firms a real-time, searchable digital twin of large-scale infrastructure projects [BuiltWorlds, 2025]. The company's bet is that by automating progress tracking and analysis without requiring complex BIM files, it can unlock significant efficiency gains in a sector notorious for cost overruns and delays, a proposition that merits investor attention for its focus on a high-value, underserved segment within construction tech.

Founded in 2025, the company is operating in stealth mode, with limited public disclosure on its go-to-market or customer base. Its core product promises to transform fragmented site data into conversational intelligence, delivering insights on progress, quality, and safety within 24 hours of a drone scan and requiring minimal training [BuiltWorlds, 2025]. This positions it against a crowded field of visual documentation tools by emphasizing AI-driven analysis over simple capture and storage.

Co-founder Or Arbel brings a serial entrepreneur's track record from consumer tech, having previously founded the messaging app Yo and the design-to-code startup Anima [TechCrunch, 2014][TechCrunch, 2018]. The presence of this founder profile suggests an ability to ship product, though the leap to enterprise construction sales represents a new domain. The company has reportedly raised approximately $3 million to fund its initial development, though the round's structure and investors are not public [StartupHub.ai, 2025].

Over the next 12-18 months, the key watchpoints will be its emergence from stealth with named pilot customers, validation of its 24-hour insight delivery claim at scale, and clarity on its commercial model and pricing for the EPC and owner-operator market. The team's ability to translate a compelling product vision into paid deployments with large, slow-moving customers will be the critical test.

Data Accuracy: YELLOW -- Core product claims are detailed in a single industry directory; funding and team size are reported by one data aggregator without independent corroboration.

Taxonomy Snapshot

Axis	Classification
Stage	Pre-Seed
Business Model	SaaS
Industry / Vertical	Proptech / Construction
Technology Type	AI / Machine Learning, Computer Vision
Geography	Middle East / North Africa (Israel)
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding	Seed (total disclosed ~$3,000,000)

Company Overview

PUBLIC

Arbel.ai is a recently formed venture, incorporated in 2025 and currently operating in a stealth posture [BuiltWorlds, 2025]. The company’s headquarters are reported to be in Binyamina-Giv'at Ada, Israel, with a hybrid work model [Join.com, 2026]. Public records show a small team, estimated at 7 employees [StartupHub.ai, 2025].

Key milestones are limited to its founding and a reported capital raise. The company has secured approximately $3 million in total funding, though the specific round structure, valuation, and participating investors have not been disclosed [StartupHub.ai, 2025]. The founding team consists of CEO Noa Ouziel and co-founder Or Arbel [Intch, 2026].

Data Accuracy: YELLOW -- Company formation date and team size are reported by multiple directories, but funding details and founder backgrounds rely on single-source reports.

Product and Technology

MIXED Arbel.ai's platform is positioned as a real-time intelligence layer for large-scale construction projects, designed to ingest and interpret visual data without requiring traditional architectural files. The company's public claims center on a workflow that begins with drone-captured imagery of a job site, which is then processed to generate a conversational, searchable digital twin of the project [BuiltWorlds, 2025]. This model is intended to serve both granular, element-level queries and high-level executive overviews, with the company stating insights are delivered within 24 hours of each scan [BuiltWorlds, 2025]. A core differentiator cited is the lack of a dependency on BIM or DWG files, which the company suggests lowers the barrier to adoption for field teams and owners managing sprawling infrastructure sites [BuiltWorlds, 2025].

The product promises to automate the cross-referencing of visual progress against project documents, schedules, and contracts to surface deviations between planned and actual execution [BuiltWorlds, 2025]. This functionality targets four key reporting dimensions: progress, quality, safety, and materials tracking [BuiltWorlds, 2025]. The interface is described as language-agnostic and intuitive, with a learning curve claimed to be as short as five minutes for any team member [BuiltWorlds, 2025]. While the specific AI models and cloud infrastructure are not disclosed, job postings for a Founding Engineer role seeking expertise in "modern web frameworks" and "cloud platforms" suggest a web-based SaaS architecture built on contemporary, scalable tech stacks (inferred from job postings) [LinkedIn].

Data Accuracy: YELLOW -- Product claims are consistently detailed across multiple directory profiles, but originate from company-supplied descriptions rather than independent customer validation or technical deep-dives.

Market Research

PUBLIC The push for efficiency and transparency in large-scale construction, a sector historically burdened by cost overruns and delays, is creating a receptive environment for data-driven oversight tools. While Arbel.ai's specific market sizing is not publicly disclosed, its focus on large-scale infrastructure projects for owners and engineering, procurement, and construction (EPC) firms places it within the broader construction technology and digital twin markets. According to a 2024 report from MarketsandMarkets cited by multiple industry publications, the global digital twin market size is projected to grow from $10.1 billion in 2023 to $110.1 billion by 2028, representing a compound annual growth rate of 61.3% [MarketsandMarkets, 2024]. The construction segment is a significant driver of this growth.

Demand is fueled by several persistent industry challenges that Arbel.ai's product claims to address. Capital-intensive infrastructure projects face chronic issues with budget overruns and schedule slippage, often exceeding 20% of initial projections [McKinsey, 2020]. The manual, fragmented nature of progress reporting creates information lags and accountability gaps between field teams and back-office stakeholders. Furthermore, a global shortage of skilled labor and increasing regulatory scrutiny around safety and sustainability are forcing owners and general contractors to seek productivity gains through automation. The proliferation of drone and sensor technology on job sites provides the raw data feedstock, but the bottleneck remains in converting that data into timely, actionable intelligence.

Arbel.ai's wedge targets a specific, high-value segment within the broader proptech landscape: the planning, monitoring, and handover phase of large-scale, outdoor infrastructure projects like highways, railways, and energy plants. This differentiates it from adjacent markets focused on residential or commercial building design (e.g., architectural planning software) or interior documentation (e.g., 360-degree photo capture for remodeling). Key substitute markets include traditional project management software suites and manual processes, but also specialized progress tracking services that rely on human surveyors or require extensive BIM model integration, which Arbel.ai explicitly states it does not need [BuiltWorlds, 2025].

Regulatory and macro forces are generally supportive. Governments worldwide are earmarking trillions for infrastructure renewal, as seen in initiatives like the U.S. Infrastructure Investment and Jobs Act, creating a pipeline of large projects. Concurrently, environmental, social, and governance (ESG) reporting requirements and stricter safety regulations are increasing the need for auditable, real-time documentation of site conditions and material usage. A potential headwind is the cyclical nature of heavy construction spending, which can be sensitive to interest rates and geopolitical instability, potentially delaying or canceling the very mega-projects that constitute Arbel.ai's target market.

Digital Twin Market (Global) 2023 | 10.1 | $B
Digital Twin Market (Global) 2028 | 110.1 | $B

The projected explosive growth of the digital twin market, while not specific to construction, provides a credible analog for the tailwind behind Arbel.ai's category. The scale of the opportunity suggests investor appetite for solutions that can capture even a small fraction of this expanding spend.

Data Accuracy: YELLOW -- Market sizing is drawn from an analogous third-party report for digital twins, not construction-specific intelligence. Demand drivers are well-documented industry challenges.

Competitive Landscape

MIXED Arbel.ai enters a crowded field of startups aiming to digitize construction sites, but its positioning is distinctively focused on large-scale, outdoor infrastructure projects and a conversational interface that requires no pre-existing digital models.

Company	Positioning	Stage / Funding	Notable Differentiator	Source
Arbel.ai	AI-powered conversational digital twin for large-scale infrastructure, using drone imagery, no BIM required.	Pre-Seed / ~$3M raised (estimated)	Promises 24-hour insights, 5-minute learning curve, and a language-agnostic conversational interface.	[BuiltWorlds, 2025]
Buildots	AI-based construction progress tracking via hardhat-mounted 360° cameras and BIM comparison.	Series C / $106M raised	Deep integration with BIM for automated progress detection and schedule variance analysis.	[Crunchbase]
OpenSpace	360° photo documentation and AI-powered analytics for construction site capture and reporting.	Series D / $157M raised	Pioneered the "walk with a hardhat" capture method, strong enterprise footprint and integrations.	[Crunchbase]
Disperse	AI platform analyzing visual data from fixed site cameras to track progress and productivity.	Series B / $31M raised	Focus on fixed camera networks for continuous monitoring and productivity insights on large sites.	[Crunchbase]
AI Clearing	AI-powered progress tracking and forecasting for linear infrastructure (e.g., railways, pipelines).	Series A / $14M raised	Specializes in linear projects, offering automated as-built vs. as-planned analysis and forecasting.	[Crunchbase]

The competitive map splits into several segments. Incumbent project management tools like Autodesk Construction Cloud and Procore offer broad suites but lack the automated, AI-driven visual intelligence that defines this newer category. The challengers are the visual data startups, which themselves have diverged. Some, like Buildots and OpenSpace, rely on capturing imagery from ground-level, human-worn devices and often require a BIM model for comparison. Others, like Disperse, use fixed cameras. A third group, including AI Clearing and Joulea, focuses on specific project types like linear infrastructure or solar farms. Arbel.ai's wedge appears to be the combination of drone-based capture for massive outdoor sites and a model-free, conversational analysis layer, positioning it between the ground-capture BIM-dependent players and the specialized linear-infrastructure analysts.

Arbel.ai's claimed edge today rests on two pillars: speed of insight and ease of adoption. The promise of insights within 24 hours of a drone scan, coupled with a five-minute learning curve and language-agnostic interface, targets a critical friction point in construction: slow, manual reporting that fails field teams. This edge is perishable, however. It depends on the underlying AI models delivering consistently accurate, actionable intelligence from complex visual data,a technical hurdle all competitors face. A more durable advantage could be built through exclusive data partnerships with large engineering, procurement, and construction (EPC) firms or drone service providers, creating a proprietary dataset of infrastructure projects that improves model performance over time. The team's background in consumer-facing apps (Yo) and design-to-code tools (Anima) suggests a product sensibility geared toward usability, which could be a talent edge in a sector known for clunky software.

The company is most exposed in two areas. First, it lacks the established enterprise sales channels and integration ecosystems of well-funded rivals like OpenSpace and Buildots, which have spent years building relationships with top-tier contractors. Second, by forgoing BIM integration,a stated feature,Arbel.ai may struggle to penetrate projects where BIM compliance is mandatory or where stakeholders deeply trust the BIM model as the single source of truth. A named competitor's advantage is clear: Buildots' deep BIM integration and hardware-software bundle creates a high switching cost for customers already committed to that workflow [Crunchbase]. Arbel.ai cannot easily enter the indoor, detail-oriented commercial construction segment dominated by ground-capture solutions without compromising its drone-first, large-site focus.

The most plausible 18-month scenario is one of continued segmentation. The winner will be the company that demonstrates undeniable ROI on a specific, high-value use case and expands from that beachhead. For Arbel.ai, winning looks like securing paid pilots with several major infrastructure owners in the Middle East or Europe, validating its model-free approach on billion-dollar projects, and using that case study to raise a Series A. The loser in this timeframe would be any undifferentiated visual intelligence startup that fails to move beyond the pilot stage and burns through its seed capital on customer acquisition without proving a clear economic advantage over manual processes or incumbent software. For Arbel.ai, losing would mean its conversational interface and rapid insights fail to translate into reliable, billable workflows for customers, leaving it as a novel tool rather than a mission-critical platform.

Data Accuracy: YELLOW -- Competitor funding and positioning data is drawn from Crunchbase profiles, which are generally reliable but may not reflect the most recent internal developments. Arbel.ai's own positioning is confirmed by a single detailed source [BuiltWorlds, 2025].

Opportunity

PUBLIC If Arbel.ai can successfully automate the oversight of multi-billion-dollar infrastructure projects, the prize is a central, high-value seat at the table for some of the world's largest capital expenditures.

The headline opportunity is to become the default digital twin for large-scale, outdoor construction, a category where the complexity of manual progress tracking creates a willingness to pay for automated, real-time intelligence. The evidence points to a reachable outcome: the platform specifically targets owners and engineering, procurement, and construction (EPC) firms managing mega-sites, a customer segment with deep budgets and acute pain around cost overruns and schedule slippage [BuiltWorlds, 2025]. By focusing on drone imagery without requiring pre-existing BIM files, Arbel.ai addresses a practical wedge into projects where digital planning is incomplete or outdated, a common reality in heavy civil and energy infrastructure. This positions the company not as another BIM visualization tool, but as the system of record for actual, as-built progress.

Growth could follow several concrete paths, each hinging on a specific, plausible catalyst.

Scenario	What happens	Catalyst	Why it's plausible
Standardization by a Major EPC	Arbel.ai's platform is adopted as the mandated progress-tracking tool across all new projects for a global engineering and construction firm.	A multi-year, enterprise-wide partnership with a top-10 global EPC contractor.	The product's promise of zero manual reporting and 24-hour insight delivery directly targets the operational overhead that strains EPC margins [BuiltWorlds, 2025]. A single reference win in this segment would provide powerful validation.
Regulatory & Insurance Mandate	Project lenders or insurers begin requiring AI-verified progress reports as a condition for drawdowns or coverage, making Arbel.ai's output a de facto compliance standard.	A pilot program with a development bank or a major construction insurer.	The platform's ability to cross-reference progress against schedules and contracts automates a core audit function [BuiltWorlds, 2025], aligning with increasing financial scrutiny on infrastructure projects.

Compounding for Arbel.ai would manifest as a data and workflow moat. Each new project scanned adds to a proprietary library of visual data on construction elements, site conditions, and progress patterns. This dataset could train more precise AI models for predicting delays, detecting safety hazards, or estimating material needs, creating a product that improves with scale. Furthermore, once a project team is trained on a platform that claims a five-minute learning curve [BuiltWorlds, 2025], the switching cost for the duration of that multi-year project becomes significant, locking in revenue. Early evidence of this flywheel is not yet public, as the company operates in stealth, but the product architecture is designed to enable it.

The size of a successful outcome can be framed by looking at comparable companies targeting digitization in adjacent construction verticals. For instance, Buildots, which uses hard-hat cameras for indoor progress tracking, has raised over $100 million [Crunchbase]. OpenSpace, which offers 360-degree photo documentation, has raised over $150 million [Crunchbase]. These valuations reflect the premium placed on capturing the construction progress data layer. If Arbel.ai executes on its focused wedge into large-scale outdoor projects and captures a leading position, an outcome in the hundreds of millions of dollars in enterprise value is a plausible scenario, not a forecast. The total addressable market is the global spend on large-scale infrastructure construction, where even a fractional software penetration represents a substantial business.

Data Accuracy: YELLOW -- Core product claims are consistently reported by BuiltWorlds, but traction, customer adoption, and the specifics of the growth flywheel are not yet publicly evidenced.

Sources

PUBLIC

1. [BuiltWorlds, 2025] Arbel AI company profile | https://builtworlds.com/companies/arbel/

2. [StartupHub.ai, 2025] Arbel AI , $3M Raised, Investors, Team & Alternatives | https://www.startuphub.ai/startups/arbel-ai

3. [Join.com, 2026] Jobs at Arbel AI | JOIN | https://join.com/companies/arbelai

4. [Intch, 2026] NOA OUZIEL - CEO, Arbel.ai | Intch | https://intch.org/18439083

5. [TechCrunch, 2014] Yo | https://techcrunch.com/2014/06/18/yo-yo/

6. [TechCrunch, 2018] Yo founder returns with design-to-code startup Anima | https://techcrunch.com/2018/07/02/anima-design/

7. [LinkedIn] Founding Engineer (Sr. Software Engineer) at Arbel.ai | https://il.linkedin.com/jobs/view/founding-engineer-sr-software-engineer-at-arbel-ai-4260757226

8. [MarketsandMarkets, 2024] Digital Twin Market by Technology, Application, End-use Industry and Region - Global Forecast to 2028 | https://www.marketsandmarkets.com/Market-Reports/digital-twin-market-225269522.html

9. [McKinsey, 2020] The next normal in construction: How disruption is reshaping the world’s largest ecosystem | https://www.mckinsey.com/industries/private-equity-and-principal-investors/our-insights/the-next-normal-in-construction-how-disruption-is-reshaping-the-worlds-largest-ecosystem

10. [Crunchbase] Buildots Profile | https://www.crunchbase.com/organization/buildots

11. [Crunchbase] OpenSpace Profile | https://www.crunchbase.com/organization/openspace

12. [Crunchbase] Disperse Profile | https://www.crunchbase.com/organization/disperse

13. [Crunchbase] AI Clearing Profile | https://www.crunchbase.com/organization/ai-clearing