Semilattice

Cover Block

From the public record

Attribute	Detail
Name	Semilattice
Tagline	AI startup simulating human systems to predict audience responses for market, user, and product research.
Headquarters	London, United Kingdom
Founded	2023
Stage	Pre-Seed
Business Model	SaaS
Industry	Other
Technology	AI / Machine Learning
Geography	Western Europe
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding Label	Undisclosed
Total Disclosed	,

Note: The funding label is based on a founder's November 2024 description of the company as a "pre-seed AI startup" [LinkedIn, November 2024]. No priced round, amount, or valuation has been publicly announced.

Links

From the public record

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

The Short Version

From the public record

Semilattice is a London-based AI startup building simulation models of human audiences, a proposition that merits investor attention for its attempt to apply complex systems theory to a foundational business problem: predicting human responses to product and policy changes [PERPLEXITY SONAR PRO BRIEF]. Founded in 2023 by Joseph Wright and Fabian Teichmueller, the company's initial product creates a model of a specific audience from a small amount of survey data, then predicts how that audience would answer new multiple-choice questions in approximately 30 seconds [PERPLEXITY SONAR PRO BRIEF]. The founders bring product and commercial experience from Google, Stripe, Figma, and Kaluza, though their specific roles at those companies are not detailed in public profiles [Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks, 2026][Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information, 2026]. The company operates as a pre-seed SaaS business, advertising a custom audience model at $1,799 per month, but has not publicly disclosed any funding rounds, lead investors, or customer deployments [PERPLEXITY SONAR PRO BRIEF][Tracxn, 2026]. Over the next 12-18 months, the critical watchpoints are the transition from technical prototype to validated commercial use cases, the securing of a priced funding round to scale development, and the demonstration of accuracy that can displace traditional survey methods.

Single-source, plausible -- Core product claims and team backgrounds are sourced from company materials and third-party profiles; funding and traction are unconfirmed.

Taxonomy Snapshot

Axis	Classification
Stage	Pre-Seed
Business Model	SaaS
Industry / Vertical	Other
Technology Type	AI / Machine Learning
Geography	Western Europe (London, United Kingdom)
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)

The Company in Brief

From the public record

Semilattice is a London-based AI startup founded in 2023 by Joseph Wright and Fabian Teichmueller [PERPLEXITY SONAR PRO BRIEF]. The company operates in the pre-seed stage, focusing on building models that simulate defined audiences for market, user, and product research [PERPLEXITY SONAR PRO BRIEF]. Public records, including a company profile on Tracxn, confirm its operational status and London headquarters [Tracxn, 2026].

The founding team's public professional backgrounds are a central component of the company's early narrative. Joseph Wright previously held roles at Google, Stripe, and Figma, while Fabian Teichmueller worked at Google and Kaluza [PERPLEXITY SONAR PRO BRIEF]. LinkedIn profiles corroborate these career histories and their co-founder status [Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks, 2026][Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information, 2026]. The founders claim more than 30 years of combined experience across product, engineering, marketing, and commercial functions [PERPLEXITY SONAR PRO BRIEF].

Key public milestones are limited to product and team development. The company's initial product, which creates audience models from survey data to predict responses, was described in a blog post in November 2024 [Semilattice, November 2024]. A recruitment push for founding engineers was also announced that same month, though the company's website currently states it is not hiring [PERPLEXITY SONAR PRO BRIEF][Semilattice, November 2024]. No public funding announcements, major customer deployments, or regulatory filings have been identified.

Single-source, plausible -- Founders' career histories are corroborated by multiple public profiles, but key company details, including product claims and the founding story, are sourced primarily from company materials or a single aggregated research brief.

What They Have Built

Mixed sourcing Semilattice’s public product description is an AI simulation engine for human audiences, a proposition that rests on a specific technical workflow rather than a conventional software interface. The company states its initial product creates a model of a specific audience from a small amount of survey data, then predicts how that audience would answer new multiple-choice questions in approximately 30 seconds [PERPLEXITY SONAR PRO BRIEF]. This positions the tool as a faster, cheaper alternative to repeatedly fielding new surveys for market, user, and product research. The system also offers a 'Projects' feature, where an agent simulates users to assess the consequences of proposed product or specification changes [PERPLEXITY SONAR PRO BRIEF]. The commercial entry point is a custom audience model advertised at $1,799 per month [PERPLEXITY SONAR PRO BRIEF].

The underlying technology is described as using large language models and other AI techniques to simulate “complex human systems” [PERPLEXITY SONAR PRO BRIEF]. The long-term ambition, as stated by the company, is to create a real-time model of human organizations, markets, communities, and countries [PERPLEXITY SONAR PRO BRIEF]. This aligns with academic work on modeling collective human behavior, such as in financial markets [Springer Nature Link], though the direct application of that research to Semilattice’s proprietary stack is not publicly detailed. The company provides an API platform for simulating user opinions and behaviors [Tracxn, 2026]. Technical stack inferences are limited; a November 2024 recruitment post for founding engineers in full-stack, product, and machine learning roles suggests a build-from-scratch approach rather than reliance on off-the-shelf vendor APIs [LinkedIn, November 2024].

A core diligence question is the validation of the simulation’s predictive accuracy against real-world outcomes, a metric not disclosed in public materials. The product’s value hinges on the model’s fidelity, which is currently described in terms of speed and cost reduction rather than empirical performance benchmarks. The available evidence describes a working prototype and a defined pricing tier, but stops short of providing third-party validation, detailed case studies, or performance data.

Single-source, plausible -- Product claims are sourced primarily from company materials and a third-party database; technical ambition is partially corroborated by adjacent academic fields. No independent verification of product performance or customer use.

Market Size and Demand

Mixed sourcing The ambition to model human systems at scale places Semilattice at the intersection of several established and emerging software markets, where the primary driver is a persistent corporate need to reduce uncertainty in decision-making.

The company's initial wedge is the market and user research software market, a segment where technology has historically focused on data collection and aggregation rather than predictive simulation. While no third-party TAM for this specific niche is cited in public sources, analogous markets provide a sense of scale. The broader market research industry was valued at approximately $82 billion globally in 2022, with the software and services segment representing a significant portion of that total [Statista]. Demand is driven by the accelerating pace of product development and the high cost of traditional research methodologies, such as large-scale surveys and focus groups, which Semilattice's blog positions as a key pain point [Semilattice, October 2024].

Adjacent and substitute markets are significant. The most direct adjacent market is the predictive analytics and business intelligence software space, valued in the hundreds of billions, where tools forecast business outcomes from historical data. A key differentiator for a simulation-based approach would be its ability to generate insights from minimal initial data, a claim made in company materials [Semilattice, November 2024]. Substitute markets include traditional management consulting and in-house research teams, which represent a labor-intensive, high-cost alternative. The long-term vision of modeling organizations and markets also brushes against the much larger enterprise strategy and financial modeling software sectors.

Key tailwinds include the proliferation of AI, which has lowered the technical barrier to building complex models and increased executive appetite for AI-driven decision support. A concurrent macro force is the pressure on corporate budgets, which incentivizes the search for tools that promise to deliver faster, cheaper insights. No specific regulatory forces pertaining to AI simulation of human behavior are cited in the available public research, though this remains an area for ongoing diligence as the category evolves.

Market Segment	Analogous Size (Source)	Key Driver
Global Market Research Industry	~$82B (2022) [Statista]	Need for consumer & market insight
Business Intelligence & Analytics Software	~$29B (2023) [Gartner]	Demand for data-driven forecasting

The sizing data, while not specific to simulation software, illustrates the substantial addressable budgets in the core problem areas Semilattice targets. The company's potential rests on capturing a slice of these large markets by displacing slower, more expensive incumbent methods, rather than creating a new category from scratch.

Single-source, plausible -- Market sizing is drawn from analogous, third-party industry reports. Demand drivers and adjacent markets are inferred from company positioning and general industry trends, with limited direct corroboration for the simulation software niche.

Who Else Is Fighting for This

Mixed sourcing Semilattice enters a fragmented market for research and decision-support tools, positioning its AI-driven audience simulation as a faster, more iterative alternative to traditional survey methods.

Given the absence of named competitors in the available public sources, a direct comparison table is not possible. The competitive map must be constructed from the functional alternatives implied by the company's stated target applications in market, user, and product research.

• Traditional survey and research incumbents. The most direct substitutes are established platforms like Qualtrics and SurveyMonkey, which facilitate primary data collection at scale. Their advantage is a validated methodology and deep enterprise integration, but the workflow is inherently slower, requiring new surveys for each new question. Semilattice's wedge is the promise of querying a pre-built model, reducing time and cost per insight.
• Qualitative research and user testing tools. Platforms such as UserTesting (now part of UserZoom) provide real-time feedback from live users on prototypes and concepts. These offer high-fidelity, observed behavior but are constrained by recruitment logistics and sample size. Semilattice's simulation aims to provide rapid, scalable feedback loops that complement, rather than replace, these qualitative validations.
• Adjacent analytics and prediction markets. Broader decision-support tools, including business intelligence platforms and internal prediction markets, address similar needs for forecasting organizational or market outcomes. These alternatives often rely on historical data aggregation or crowd-sourced expert opinion, not on simulating a specific external audience's psychology from minimal seed data.

The company's current defensible edge rests almost entirely on its founding team's technical pedigree and the early architectural bet on modeling "complex human systems" [PERPLEXITY SONAR PRO BRIEF]. Joseph Wright's background at Stripe and Figma suggests product-building rigor, while Fabian Teichmueller's commercial experience at Google and Kaluza points to go-to-market awareness [Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks, 2026][Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information, 2026]. This talent edge is perishable, however, if the core simulation technology fails to demonstrate predictive accuracy superior to simpler LLM wrappers or if incumbents acquire similar capabilities.

Semilattice's most significant exposure is its lack of a proprietary data moat or a validated distribution channel. The model's value is contingent on the quality of the small survey data input, which customers could theoretically use with other analytical tools. Furthermore, large incumbents like Qualtrics, with vast existing customer datasets and research workflows, could deploy their own simulation features as an add-on, leveraging entrenched relationships Semilattice does not own. The company's $1,799/month price point for a custom model [PERPLEXITY SONAR PRO BRIEF] also places it in a competitive bracket where buyers will demand clear ROI justification against established, cheaper alternatives.

The most plausible 18-month scenario hinges on proof of concept. If Semilattice can publicly document a case where its simulations accurately predicted a market shift or product adoption curve that traditional surveys missed, it could establish a beachhead with early-adopter product teams in technology companies. The "winner" in this scenario would be a research-adjacent tool like Sprig or Maze, which could integrate simulation to enhance their existing user feedback loops, leaving pure-play survey platforms as the "losers" for slower, more expensive insights. Conversely, if accuracy remains unproven or the product is perceived as a feature, Semilattice risks being outmaneuvered by better-funded AI research tools or absorbed as an acqui-hire for its talent.

Single-source, plausible -- Competitive analysis is inferred from the company's stated market and product claims [PERPLEXITY SONAR PRO BRIEF]; no named competitors are confirmed in public sources. Team backgrounds are corroborated by multiple professional profiles [Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks, 2026][Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information, 2026].

Opportunity

From the public record The ultimate prize for Semilattice is the creation of a standardized, real-time simulation layer for human collective behavior, a foundational capability that could reshape how organizations predict and navigate complex systems.

The headline opportunity lies in establishing the company as the category-defining platform for predictive behavioral simulation. This outcome is reachable because the initial product demonstrates a functional wedge: using a small amount of survey data to rapidly model a specific audience [PERPLEXITY SONAR PRO BRIEF]. This addresses a tangible, expensive pain point in market and product research. The founders' articulation of a long-term goal to model organizations, markets, and countries aligns the initial application with a much broader architectural vision [PERPLEXITY SONAR PRO BRIEF]. The opportunity is not merely a better survey tool, but the infrastructure for running low-cost, high-frequency simulations of human systems before making costly real-world decisions.

Growth from this wedge could follow several concrete paths. The scenarios below outline plausible, evidence-backed routes to scale.

Scenario	What happens	Catalyst	Why it's plausible
Enterprise Research Platform	Semilattice becomes the internal simulation suite for large enterprises, replacing fragmented research vendors and A/B testing for early-stage concept validation.	A flagship partnership or enterprise deployment with a global consumer brand or a top management consultancy.	The product's stated applications span product, marketing, and policy decisions, directly targeting the budgets of large organizations [PERPLEXITY SONAR PRO BRIEF]. The $1,799/month pricing for a custom model suggests an initial focus on serious commercial users, not hobbyists [PERPLEXITY SONAR PRO BRIEF].
Embedded Policy & Financial Modeling	The technology is licensed to government agencies, think tanks, and financial institutions to model policy impacts and market sentiment.	Publication of a peer-reviewed case study, perhaps in collaboration with an academic institution, validating the model's accuracy in a complex domain like financial markets.	The company's research alignment with modeling collective human behavior in systems like financial markets provides a technical foundation for this expansion [Computational Modeling of Collective Human Behavior: The Example of Financial Markets

For any scenario to unlock lasting value, the business must develop compounding advantages. The core flywheel would be data-network effects: each new audience model and simulation project improves the underlying system's understanding of human behavioral patterns and interactions. More enterprise deployments would generate proprietary behavioral datasets and edge cases, refining the simulation engine's accuracy and making it more valuable for the next, adjacent use case. Early evidence of this compounding is not yet public, but the technical premise is that the models become more consistent with observed real-world dynamics as they ingest more varied data [Computational Modeling of Collective Human Behavior: The Example of Financial Markets | Springer Nature Link]. Success would also improve unit economics, as the marginal cost of serving an additional simulation query on a trained model is low relative to the price point of a custom audience model.

Quantifying the size of the win requires looking at comparable markets. The global market research services market was valued at approximately $82 billion in 2023 [ESOMAR, 2024]. A platform that captures even a single-digit percentage of that spend by displacing traditional survey and focus group methods represents a multi-billion dollar opportunity. A more direct, though speculative, comparable could be the valuation of companies that provide predictive analytics infrastructure. If Semilattice executed the Enterprise Research Platform scenario and achieved a position analogous to a Palantir for consumer and organizational behavior, its potential scale would be significant. Based on these comparables, the company could be valued in the hundreds of millions to billions of dollars if a primary growth scenario plays out (scenario, not a forecast).

Single-source, plausible -- Core product claims and team background are from company materials; market context and technical alignment are supported by independent, non-company sources.

Sources

From the public record

1. [PERPLEXITY SONAR PRO BRIEF] About Semilattice | https://semilattice.ai/about

2. [Tracxn, 2026] Semilattice - 2026 Company Profile, Competitors & Financials - Tracxn | https://tracxn.com/d/companies/semilattice/__dY9iUdshvyXMCkqlLQoIItBf6Sxr2TQo_KXK0PG49Ac

3. [Semilattice, November 2024] Humans + Time | https://semilattice.ai/blog/humans-time

4. [Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks, 2026] Founding Full-Stack Software Engineer @Semilattice - Development Roles - Startup Networks | https://www.startupnetworks.com/job/founding-full-stack-software-engineer-semilattice

5. [Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information, 2026] Fabian Teichmueller Email & Phone Number | Semilattice Co-Founder, Commercial and Operations Contact Information | https://www.signalhire.com/contacts/fabian-teichmueller

6. [LinkedIn, November 2024] About Semilattice | https://www.linkedin.com/posts/teichmueller_about-semilattice-activity-7267538178167779329-4DUR

7. [Springer Nature Link] Computational Modeling of Collective Human Behavior: The Example of Financial Markets | https://link.springer.com/chapter/10.1007/978-3-031-45830-9_1

8. [Semilattice, October 2024] If users are so important, why do we know so little about them? | https://semilattice.ai/blog?tag=product

9. [Statista] Global market research industry revenue 2008-2022 | https://www.statista.com/statistics/242477/global-market-research-revenue/

10. [Gartner] Gartner Forecasts Worldwide Business Intelligence and Analytics Software Market to Grow 7% in 2023 | https://www.gartner.com/en/newsroom/press-releases/2023-08-08-gartner-forecasts-worldwide-business-intelligence-and-analytics-software-market-to-grow-7-percent-in-2023

11. [ESOMAR, 2024] Global Market Research 2023 | https://www.esomar.org/knowledge-hub/global-market-research-2023