Semble AI

Cover Block

PUBLIC

Name	Semble AI
Tagline	AI automation for code-compliant building system design in construction [Semble AI, 2025]
Headquarters	San Francisco, CA, USA [Y Combinator, 2025]
Founded	2025 [Y Combinator, 2025]
Stage	Seed [Y Combinator, 2025]
Business Model	SaaS
Industry	Proptech
Technology	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding Label	Undisclosed (total disclosed ~$500,000) [Y Combinator, 2025][Wikipedia, 2026]

Links

PUBLIC

• Website: https://www.sembleai.com/
• LinkedIn: https://www.linkedin.com/company/sembleai/
• Y Combinator: https://www.ycombinator.com/companies/semble-ai

Executive Summary

PUBLIC Semble AI automates the design of building systems like fire suppression and HVAC for construction firms, a process currently reliant on manual drafting and spreadsheets, by applying AI to generate code-compliant layouts and project estimates [Perplexity Sonar PRO BRIEF, 2025]. The company's early-stage appeal lies in its direct attack on a documented inefficiency within a large, established market, paired with the validation signal of its Y Combinator selection. Founded in 2025 by Stanford computer science graduates Jonathan Tyshler and Ethan Boyers, the company emerged from the founders' recognition of the slow, error-prone nature of traditional building system design [Y Combinator, 2025]. The core product promises to transform workflows that can take hundreds of engineering hours into automated processes completed in a few hours, starting with fire and life-safety systems [Semble AI website, 2025]. Tyshler's prior experience at Convergint, a building systems integrator, provides relevant domain insight, while Boyers' technical background anchors the AI development effort [RocketReach, 2026]. The company is backed by Y Combinator's F25 batch, with an initial seed round of $500,000 reported, operating on a SaaS model [Wikipedia, 2026]. Over the next 12-18 months, the key watchpoints will be the transition from technical development to named customer deployments, the validation of its code-compliance claims in real projects, and the expansion from its initial fire suppression wedge into adjacent mechanical and plumbing systems.

Data Accuracy: YELLOW -- Core company facts and YC backing are confirmed; market size and product capability claims are sourced from a single brief or the company's own website.

Taxonomy Snapshot

Axis	Classification
Stage	Seed
Business Model	SaaS
Industry / Vertical	Proptech
Technology Type	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding	Undisclosed (total disclosed ~$500,000)

Company Overview

PUBLIC

Semble AI was founded in 2025 by Stanford computer science graduates Jonathan Tyshler and Ethan Boyers [Y Combinator, 2025]. The company is headquartered in San Francisco, California, and operates as a private entity, though its specific legal structure is not detailed in public filings. The founding narrative centers on applying AI to a complex, manual domain one of the founders knew from prior work, with Tyshler having experience at building systems integrator Convergint [RocketReach, 2026].

The company's primary public milestone to date is its acceptance into the Y Combinator F25 batch, announced in 2025 [Y Combinator, 2025]. This accelerator program serves as the company's launchpad and sole disclosed source of institutional backing. No other corporate milestones, such as a commercial product launch or named customer deployments, have been announced.

Data Accuracy: YELLOW -- Foundational facts (founding year, HQ, YC participation) are confirmed by YC and Crunchbase. Team background details are partially corroborated by LinkedIn and RocketReach, but some sources have lower confidence.

Product and Technology

MIXED

Semble AI's product is defined by a specific and ambitious claim: to automate the design of complex building systems, turning a process that can take hundreds of hours of manual engineering work into a task measured in hours [Semble AI, 2025]. The company's public materials focus on fire suppression, HVAC, plumbing, and security systems, promising to generate code-compliant device layouts, bills of materials, cost estimates, and client proposals [Perplexity Sonar PRO BRIEF, 2025]. The initial market wedge appears to be fire and life-safety systems [Crunchbase, 2025]. The core value proposition is not just speed, but the integration of localized building codes into the automated workflow, a critical pain point in a fragmented, regulation-heavy industry.

The underlying technology stack is not detailed in public sources. [PUBLIC] The company's hiring page indicates an active search for engineering roles, which suggests a focus on building a robust technical foundation [Y Combinator, 2025]. (inferred from job postings) The requirement to parse architectural plans, apply complex and varying municipal codes, and output precise technical schematics points toward a system combining computer vision, knowledge graphs of building regulations, and generative design algorithms. No public demos, case studies, or detailed technical whitepapers have been released to substantiate the 300-hour-to-3-hour workflow transformation claim, which remains a company-stated aspiration rather than a verified metric.

Data Accuracy: YELLOW -- Product claims are sourced from the company website and a Y Combinator profile; technical capabilities and performance metrics are unverified by third parties.

Market Research

PUBLIC

The opportunity for automation in construction system design is driven by a persistent labor shortage and a growing backlog of projects, which forces firms to seek productivity gains wherever they can find them. Semble AI targets the building-system integration market, which a third-party brief valued at $600 billion globally [Perplexity Sonar PRO BRIEF, 2025]. This figure encompasses the design, installation, and integration of mechanical, electrical, and plumbing (MEP) systems, including fire suppression, HVAC, plumbing, and security. While the company's specific serviceable addressable market (SAM) is not publicly defined, the broader construction technology market is a relevant analog, with McKinsey estimating its value at over $300 billion annually (analogous market, McKinsey) [McKinsey].

Demand for automated design tools is propelled by several structural tailwinds. The construction industry faces a well-documented shortage of skilled engineers and drafters, which extends project timelines and increases costs. Simultaneously, building codes are becoming more complex and localized, raising the compliance burden on design teams. These pressures create a clear incentive for contractors and system integrators to adopt software that can compress design cycles and reduce error rates. The push for more sustainable and energy-efficient buildings also adds layers of design complexity that favor computational solutions over manual methods.

Key adjacent markets include broader construction management software, estimated at $10.9 billion in 2023 and projected to grow to $19.1 billion by 2028 (analogous market, MarketsandMarkets) [MarketsandMarkets], and the computer-aided design (CAD) software market, valued at approximately $11.5 billion (analogous market, Grand View Research) [Grand View Research]. These markets represent both potential expansion vectors and the competitive landscape for design workflow tools. A direct substitute for Semble AI's proposed service is the continued reliance on in-house engineering teams using legacy CAD and BIM (Building Information Modeling) software, supplemented by spreadsheets for calculations and code checks.

Regulatory forces are a double-edged sword, acting as both a barrier and a catalyst. Strict, jurisdiction-specific building codes for fire and life-safety systems create a high compliance hurdle that any automation tool must clear, which can slow adoption. However, this same complexity is a primary pain point that makes manual design so costly and time-consuming, thereby strengthening the value proposition for a code-aware AI solution. Macroeconomic cycles in construction spending introduce volatility, but the underlying need for renovation, retrofitting, and infrastructure development in North America provides a steady baseline of demand.

Total Building-System Integration Market | 600 | $B

The cited $600 billion market size suggests a substantial total addressable market, though it is a broad, top-down figure that includes hardware, labor, and services far beyond software design. The more immediate opportunity lies in capturing a fraction of the design and engineering services spend within that larger pie.

Data Accuracy: YELLOW -- Market sizing from a single third-party brief; adjacent market sizes from analogous industry reports.

Competitive Landscape

MIXED Semble AI enters a market defined by manual processes and fragmented software tools, positioning its AI agents as a direct replacement for incumbent design workflows rather than a feature within existing platforms.

A direct, named competitor is not yet present in public sources. The competitive analysis therefore focuses on mapping the broader ecosystem of alternatives and substitutes.

• Incumbent design software. Established platforms like Autodesk (Revit) and Trimble provide the foundational CAD and BIM environments where manual design occurs. These are not direct competitors but represent the entrenched workflow Semble aims to automate. Their advantage is universal adoption and deep integration with other construction software; their exposure is reliance on human expertise for system-specific layouts.
• Specialized engineering consultants. The labor market itself is a competitor, comprising MEP (mechanical, electrical, plumbing) and fire protection engineering firms. These consultants offer code-compliant design as a service. Their edge is deep regulatory experience and client trust; their vulnerability is high cost and scalability limits.
• Adjacent construction tech. A wave of startups is applying AI to various construction tasks, from layout planning (e.g., OpenSpace, Dusty Robotics for site work) to scheduling (e.g., ALICE Technologies). These companies operate in parallel lanes, automating different slices of the project lifecycle. The risk for Semble is that a well-funded player in an adjacent category could expand horizontally into system design.
• Potential future entrants. Large generalist AI platforms (e.g., OpenAI, Anthropic) or building information modeling suites could theoretically develop similar agents. Their distribution and capital would be formidable, but they lack the domain-specific training data and nuanced understanding of local building codes that Semble is building [Perplexity Sonar PRO BRIEF, 2025].

Semble's claimed edge rests on two pillars: automation specificity and regulatory navigation. The company is not building a general-purpose design tool but agents trained explicitly on fire suppression and security system logic. This focus, coupled with the founders' background in system integration, aims to create a product that understands the constraints of the National Fire Protection Association (NFPA) codes or International Building Code (IBC) sections relevant to its niche. This regulatory moat is perishable, however, if a competitor with greater resources can license or scrape equivalent code datasets and hire similar domain experts.

The company's most significant exposure is its lack of an owned distribution channel. It must sell into construction firms or integrators that are already customers of Autodesk or specialized consultancies. A competitor with an existing large installed base,imagine Autodesk launching a similar AI module as an add-on to its Revit subscriptions,could use its channel to capture the market rapidly. Semble's success hinges on moving faster to prove ROI before incumbents mobilize.

The most plausible 18-month scenario involves segmentation by system type. A "winner" could emerge in the fire suppression niche if Semble secures early partnerships with major sprinkler contractors or insurers, using those deployments to train a uniquely robust agent. A "loser" in this timeframe would be any new entrant that attempts a broader "full MEP" AI solution without deep vertical expertise, struggling with the complexity of mechanical and plumbing codes and failing to gain traction in any single segment.

Data Accuracy: YELLOW -- Competitive mapping is inferred from market structure and cited product claims; no direct competitor profiles are publicly confirmed.

Opportunity

PUBLIC The prize for automating the design of building systems is a significant share of the $600 billion integration market currently managed through manual, error-prone processes [Perplexity Sonar PRO BRIEF, 2025].

The headline opportunity is to become the default design layer for all building systems, a category-defining platform that sits between architectural plans and physical installation. The outcome is reachable because the problem is a known bottleneck. Construction firms and system integrators currently rely on spreadsheets and manual drafting to design fire suppression, HVAC, plumbing, and security systems, a process that can span weeks and is subject to local code interpretation [Perplexity Sonar PRO BRIEF, 2025]. Semble AI's wedge into fire and life-safety systems targets a critical, code-intensive subsystem where automation can deliver immediate ROI in time and compliance risk. The founders' specific background in building systems integration, with CEO Jonathan Tyshler's prior role at Convergint, provides domain credibility for navigating this complex, fragmented space [Y Combinator, 2025].

Two or three growth scenarios, each named

Scenario	What happens	Catalyst	Why it's plausible
Dominant Design Tool	Becomes the standard software for MEP (Mechanical, Electrical, Plumbing) and fire safety engineers at top 100 construction firms.	A major general contractor or engineering firm publicly adopts the tool for a flagship project, validating its code-compliance engine.	The company's initial focus on code-compliant outputs directly addresses a primary pain point of liability and rework [Crunchbase, 2025]. Y Combinator's network provides a credible launchpad for securing such a lighthouse customer.
Embedded System Integrator API	The AI design engine is licensed and embedded into the workflow software of large building system manufacturers (e.g., Johnson Controls, Siemens).	A strategic partnership with a major manufacturer to power the design module of their own customer-facing software.	The product's claimed output,device layouts, bills of materials, and cost estimates,aligns with the core deliverables of manufacturer design tools [Perplexity Sonar PRO BRIEF, 2025]. An API model would allow rapid, capital-light scaling.

What compounding looks like The primary compounding mechanism is a data moat built on code compliance. Each project completed using Semble AI generates a verified, approved design for a specific building type in a specific jurisdiction. This corpus of validated designs would train the AI to handle an increasing variety of codes and edge cases more accurately than new entrants. The company's website claims the tool delivers "full code compliance and AHJ (Authority Having Jurisdiction) approval" [Semble AI, 2025], suggesting the product roadmap is oriented toward building this verification layer. Early adoption by system integrators, the stated target customer, would feed this loop with real-world project data, continuously improving the model's accuracy and trustworthiness.

The size of the win A credible comparable is the valuation of public computer-aided design (CAD) and building information modeling (BIM) software leaders. Autodesk, which serves the broader architecture, engineering, and construction (AEC) industry, currently holds a market capitalization exceeding $50 billion. While Semble AI operates in a more specialized niche, a successful outcome as the dominant design tool for building systems could support a multi-billion dollar valuation. For context, capturing just 5% of the cited $600 billion integration market's software spend would represent a $30 billion addressable market. If the "Dominant Design Tool" scenario plays out, the company could be valued on a revenue multiple similar to high-growth vertical SaaS peers, which have historically traded between 10x and 20x forward revenue. This is a scenario-based outcome, not a forecast.

Data Accuracy: YELLOW -- Market size and product claims are cited from secondary briefs and the company website; founder backgrounds are corroborated by YC and LinkedIn.

Sources

PUBLIC

1. [Semble AI, 2025] Semble AI - AI-Powered Building System Design | https://www.sembleai.com/

2. [Y Combinator, 2025] Semble AI: Autonomous building-system design for construction companies. | https://www.ycombinator.com/companies/semble-ai

3. [Crunchbase, 2025] Semble AI - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/semble-ai

4. [Perplexity Sonar PRO BRIEF, 2025] Perplexity Sonar PRO BRIEF |

5. [Wikipedia, 2026] Y Combinator - Wikipedia | https://en.wikipedia.org/wiki/Y_Combinator

6. [RocketReach, 2026] Jonathan Tyshler Email & Phone Number | Semble AI (YC F25) CEO Contact Information | https://rocketreach.co/jonathan-tyshler-email_836755127

7. [McKinsey] McKinsey |

8. [MarketsandMarkets] MarketsandMarkets |

9. [Grand View Research] Grand View Research |

10. [LinkedIn, 2026] Ethan Boyers - CTO @ Semble AI (YC F25) | Stanford Math ... | https://www.linkedin.com/in/ethan-boyers/