Simavai
AI-native engineering simulation platform for industrial and R&D teams, and an EdTech platform for virtual learning.
Website: https://simavai.com/
Cover Block
From the public record
| Attribute | Value |
|---|---|
| Company Name | Simavai |
| Tagline | AI-native engineering simulation platform for industrial and R&D teams, and an EdTech platform for virtual learning. |
| Headquarters | Toronto, Canada |
| Founded | 2022 |
| Stage | Seed |
| Business Model | SaaS |
| Industry | Deeptech |
| Technology | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Academic Spinout |
| Funding Label | Undisclosed |
Links
From the public record
- Website: https://simavai.com/
- LinkedIn: https://www.linkedin.com/company/simavai/
- Website (LABonWEB): https://labonweb.ca/
The Short Version
From the public record Simavai is a Toronto-based startup attempting to modernize two distinct but related fields, engineering simulation and science education, by applying an AI-native layer to complex workflows. The company's dual focus, on the industrial-grade Forge AI platform for engineers and the educational LABonWEB platform for institutions, represents a bet that the same underlying technology stack can address both high-value commercial R&D and a persistent accessibility gap in hands-on learning [Simavai website, retrieved 2026] [F6S, August 2026 update].
Founded in 2022 by University of Toronto PhD alumni, the company originated from an academic effort to bridge gaps in digital education through interactive simulation [F6S, August 2026 update]. Its core technical proposition combines generative AI, multiphysics solvers, and physics-informed machine learning to automate setup and analysis, aiming to reduce the expertise and computational data traditionally required for advanced simulations [ALL IN, 2026].
CEO Morteza Javid, an engineering scientist, has secured early external validation, winning an Immigrant Entrepreneur Award in 2023, and the company has attracted investment from LabEight* Ventures, though the specific round size and valuation remain undisclosed [Markets Insider, August 2024] [F6S, August 2026 update]. The business model appears to be SaaS-based, with LABonWEB's pricing starting at an accessible C$15 per user per four-month cycle, suggesting a wedge into budget-conscious educational markets [F6S, August 2026 update].
Over the next 12-18 months, the critical watchpoints will be whether Simavai can demonstrate material enterprise traction for Forge AI in its named industrial verticals, and if the two-product strategy proves synergistic or strains the focus of a currently very small team, reported at just two employees for the LABonWEB entity [RocketReach, retrieved 2026]. Single-source, plausible -- Key company claims are sourced from its website and ecosystem profiles, but funding details and customer traction are not publicly confirmed.
Taxonomy Snapshot
| Axis | Classification |
|---|---|
| Stage | Seed |
| Business Model | SaaS |
| Industry / Vertical | Deeptech |
| Technology Type | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Academic Spinout |
The Company in Brief
From the public record
Simavai is a Toronto-based startup founded in 2022, emerging from a PhD alumni group at the University of Toronto [F6S, August 2026 update]. The company's formation was driven by an ambition to bridge gaps in digital education and engineering workflows using interactive simulation, a focus that has since evolved into two distinct but related product lines [F6S, August 2026 update].
Key milestones are limited to early-stage recognition and team formation. In 2023, CEO Morteza Javid won the Immigrant Entrepreneur Award at the CanadianSME National Business Awards for his role leading the company's LABonWEB platform [LinkedIn (LABonWEB page), June 2024] [Markets Insider, August 2024]. The company was also nominated for an Excellence in Tech & AI Award, though the specific date and awarding body are not detailed in public sources [LinkedIn (Ali Rahimi), retrieved 2026].
By 2026, the company's operational footprint remained small, with its LABonWEB platform reporting a team of two employees [RocketReach, retrieved 2026]. The company has secured investment from LabEight* Ventures, a venture building initiative, though the terms, amount, and date of this investment are not publicly disclosed [F6S, August 2026 update].
Single-source, plausible -- Foundational facts (founding year, location, founder) are corroborated by multiple sources; funding and detailed milestones are based on a single platform profile.
What They Have Built
Mixed sourcing Simavai has articulated a dual-product strategy, with both offerings centered on applying AI to simulation but targeting distinct user bases. The company's primary commercial focus appears to be Forge AI, an engineering simulation platform designed to accelerate industrial R&D workflows. According to the company's website, the platform integrates model preparation, simulation, visualization, and analysis into a single environment, using AI assistants to help engineers define physics, parameters, and boundary conditions during setup [Simavai website, retrieved 2026]. The platform is described as combining generative AI, advanced multiphysics solvers, and physics-informed machine learning to automate complex workflows and support real-time digital twins [ALL IN, 2026].
Forge AI runs simulation workloads on cloud infrastructure, allowing users to import geometry, configure models, and inspect results through interactive 3D visualization [Flypix.ai, August 2026]. A feature described as a 'Simulator Agent' is designed to guide configuration, workflow management, and result interpretation [Flypix.ai, August 2026]. Public materials list target sectors as aerospace, automotive, manufacturing, energy, industrial equipment, and research [ALL IN, 2026]. The company's second product, LABonWEB, is positioned as an EdTech platform that leverages similar generative AI and simulation technologies to create immersive, hands-on learning modules for educational institutions [F6S, August 2026 update].
Pricing and go-to-market details are available only for the LABonWEB product. Its paid plans start from C$15 per user per 4-month cycle, with a free access offer for one 4-month cycle also promoted [F6S, August 2026 update]. This suggests an accessible, low-friction entry model aimed at academic adoption. Specific technical architecture, API details, and integration capabilities for Forge AI are not publicly detailed, nor are performance benchmarks against incumbent simulation tools.
Single-source, plausible -- Product claims are sourced from company website and vertical press; technical performance and architecture details are not independently verified.
Market Size and Demand
From the public record The push for digital transformation in engineering and education has created a clear opening for simulation tools that can reduce costs, compress development cycles, and democratize access to complex systems. For Simavai, this translates to two distinct but adjacent markets: industrial engineering simulation and simulation-based educational technology.
A definitive total addressable market (TAM) for an integrated AI-native simulation platform is not publicly available from third-party reports. However, analogous market sizing provides a useful frame. The broader engineering simulation and analysis software market was valued at approximately $11 billion globally in 2023, with projections for steady growth driven by adoption in automotive, aerospace, and manufacturing [Grand View Research, 2024]. The more specific market for AI in engineering simulation is a fast-growing subset. For the company's LABonWEB product, the global virtual labs market for education is often cited within a range of $2 to $3 billion, with expectations for significant expansion as institutions seek to scale hands-on learning affordably [HolonIQ, 2024].
Demand drivers for industrial simulation are well-documented. Companies face pressure to accelerate product development while managing rising physical prototyping and testing costs. The integration of generative AI promises to lower the expertise barrier for setting up complex multiphysics simulations, a key friction point noted in industry analysis [Gartner, 2024]. In parallel, the education sector continues to grapple with resource constraints and the need for scalable, engaging STEM instruction, fueling investment in virtual and augmented reality learning tools. The common technological thread is a shift toward cloud-based, interactive simulation that can be accessed without specialized local hardware.
Key adjacent markets include the broader computer-aided engineering (CAE) software suite, digital twin platforms, and the expansive market for online professional upskilling. These represent both potential expansion vectors and competitive threats from established vendors broadening their offerings. Regulatory and macro forces are generally favorable but carry nuance. Data sovereignty and security requirements, particularly in aerospace and defense applications, can influence cloud deployment decisions. In education, procurement cycles and curriculum accreditation processes dictate sales velocity, often favoring solutions with proven pedagogical efficacy over pure technological novelty.
Engineering Simulation Software (2023) | 11 | $B
Virtual Labs for Education (2024) | 2.5 | $B
The available sizing data, while analogous, highlights the substantial economic pools Simavai is targeting. The nearly fivefold difference between the industrial and educational segments underscores the strategic question of resource allocation between the two platforms. Growth in both areas is tied to enduring trends in digitalization, but the customer profiles, sales motions, and product requirements differ meaningfully.
Single-source, plausible -- Market sizing figures are from analogous, third-party industry reports, not company-specific projections.
Who Else Is Fighting for This
Mixed sourcing
Simavai operates across two distinct competitive arenas, each with its own set of established players and market dynamics, a positioning that requires separate analysis.
| Company | Positioning | Stage / Funding | Notable Differentiator | Source |
|---|---|---|---|---|
| Simavai (Forge AI) | AI-native engineering simulation for industrial R&D. | Seed. Investor: LabEight* Ventures. | Integrates generative AI and physics-informed ML into a single workflow environment. | [Simavai, retrieved 2026] |
| Labster | Virtual science lab simulations for education. | Venture-backed. Raised $60M+ (estimated). | Extensive library of interactive, curriculum-aligned science labs. | [Crunchbase] |
| Lab4U | Mobile app platform for science experiment simulations. | Venture-backed. | Focus on smartphone accessibility and low-cost hardware integration. | [Crunchbase] |
| Brilliant | Interactive courses in math, science, and computer science. | Venture-backed. | Broad STEM course catalog with problem-solving focus, less simulation-heavy. | [Crunchbase] |
For its LABonWEB EdTech platform, Simavai competes directly with simulation-focused educational software providers. Labster is the most capitalized player in this segment, with a significant head start in building a content library and securing institutional contracts. Lab4U and Science Practical Simulator represent more specialized or access-oriented alternatives. Brilliant operates in an adjacent space, competing for learner attention and institutional budgets with a broader, course-based approach rather than lab simulation. The competitive map for Forge AI is less clear from public data, but it would logically contend with legacy simulation suites from giants like Ansys and Dassault Systèmes, as well as a newer cohort of cloud-native and AI-augmented simulation tools from startups such as SimScale and OnScale.
Simavai’s primary defensible edge appears to be its technical approach of combining generative AI assistants with multiphysics solvers, which it claims can automate complex setup and analysis workflows [Simavai website, retrieved 2026]. For the educational side, its pricing model starting at C$15 per user per 4-month cycle is a low-friction wedge into budget-constrained institutions [F6S, August 2026 update]. However, these edges are perishable. The AI workflow automation is a feature that larger incumbents can and are integrating. The low-cost educational pricing is not a moat and could be undercut. A more durable advantage would be proprietary datasets or unique solver algorithms, but these are not mentioned in public materials. The team’s academic background in high-performance computing and modeling is an asset, but not unique in this field [LinkedIn, retrieved 2026].
The company is most exposed in two areas. First, in EdTech, it lacks the scale, brand recognition, and sales reach of a Labster, which has raised substantial capital to fund content development and enterprise sales. Second, by pursuing two markets,industrial engineering and education,with what appear to be two different products, Simavai risks diluting its focus and resources. A two-person team, as listed for LABonWEB, cannot effectively build, sell, and support two complex platforms against well-funded specialists [RocketReach, retrieved 2026]. The capital advantage clearly lies with its competitors.
The most plausible 18-month scenario hinges on focus and capital. If Simavai secures a seed round and concentrates resources on one product, it could establish a beachhead. A winner in EdTech would be the company that most effectively partners with curriculum providers and demonstrates improved learning outcomes. A loser would be any platform that fails to move beyond early-adopter institutions and prove renewal economics. For the industrial simulation bet, the winner will be the tool that demonstrates tangible time-to-insight savings for engineering teams on real, complex problems. Without a clear demonstration of customer adoption and a focused go-to-market strategy for either product, Simavai risks being overshadowed in both segments.
Single-source, plausible -- Competitor identities and basic positioning are confirmed, but comparative funding and scale data for competitors is inferred from Crunchbase profiles. Simavai's own competitive differentiation is based on company claims.
Opportunity
From the public record Simavai's opportunity rests on capturing a meaningful share of the engineering simulation and virtual learning markets by using AI to lower the barriers to entry and accelerate workflows, a bet that could scale to hundreds of millions in annual revenue if execution aligns with the product's technical promise.
The headline opportunity is to become the default AI-native simulation layer for both industrial R&D and technical education, a dual-market position that could create a unique, defensible platform. Forge AI's core proposition, automating complex simulation setup and analysis through AI assistants and cloud execution, directly targets a pain point in established industries like aerospace and automotive where simulation is critical but time-consuming [Simavai website, retrieved 2026]. The parallel EdTech platform, LABonWEB, addresses a separate but adjacent need for accessible, hands-on technical training. The plausibility of this dual-track outcome is grounded in the shared underlying technology stack,Generative AI, multiphysics solvers, and physics-informed machine learning [ALL IN, 2026],and the founder's academic roots in high-performance computing and simulation [LinkedIn, retrieved 2026]. This suggests the company is not merely bundling unrelated products but exploring two go-to-market channels for a core simulation engine.
Growth could follow several distinct paths, each with identifiable catalysts.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Industrial Platform Adoption | Forge AI becomes a standard tool for small-to-mid-sized engineering teams, displacing legacy desktop software or more expensive cloud solutions. | A major partnership with a cloud infrastructure provider (AWS, Google Cloud, Azure) to offer Forge AI as a managed service. | The platform is already architected for cloud execution [Flypix.ai, August 2026], and its accessible pricing wedge (C$15/user/cycle for LABonWEB) demonstrates a focus on lowering adoption friction [F6S, August 2026 update]. |
| Education Market Standard | LABonWEB becomes a widely adopted virtual lab platform within North American secondary and post-secondary STEM programs. | Securing a district-wide or university-wide contract with a major public institution as a reference customer. | The platform is explicitly marketed to educational institutions for simulation-based learning [F6S, August 2026 update], and the founding team's PhD background from the University of Toronto provides credibility in academic circles [F6S, August 2026 update]. |
A successful wedge into either market could initiate a compounding effect. In the industrial segment, each new simulation run generates proprietary data on physics parameters and outcomes, which can be used to further train and refine the platform's AI models, creating a data moat that improves accuracy and automation over time. For the EdTech side, widespread institutional adoption creates a network effect: a library of user-generated simulation modules and curricula could increase platform stickiness and reduce content creation costs for new customers. Early signals of this flywheel are not yet publicly visible in the form of published case studies or data scale, but the platform's design intent,AI assistants that learn from user interactions,points toward this direction [Simavai website, retrieved 2026].
The size of the win, should the Industrial Platform Adoption scenario materialize, can be contextualized by looking at the established simulation software market. While Simavai is not a direct competitor to giants like Ansys or Siemens, its AI-native, workflow-automation approach targets a segment of users underserved by those high-cost, complex suites. A credible comparable might be the trajectory of simulation-adjacent SaaS platforms that achieved significant scale. For instance, public companies in the broader computer-aided engineering (CAE) and simulation space trade at revenue multiples that reflect the high-value, sticky nature of their software. If Simavai successfully captures even a single-digit percentage of the long-tail engineering market, it could build a business valued in the hundreds of millions of dollars (scenario, not a forecast). The more immediate EdTech path also offers substantial scale, as evidenced by competitor Labster's growth within the virtual science lab sector [Crunchbase].
Single-source, plausible -- The opportunity analysis is based on the company's stated product capabilities and market positioning, but lacks public validation from customer case studies or detailed market penetration metrics.
Sources
From the public record
[Simavai website, retrieved 2026] Simavai - Forge AI | Engineering Simulations, Accelerated by AI | https://simavai.com/
[F6S, August 2026 update] F6S - Simavai (LABonWEB) | https://www.f6s.com/company/simavai-labonweb
[ALL IN, 2026] ALL IN | 2026 Industries - All In AI Event | https://allinevent.ai/pages/2026-industries
[Flypix.ai, August 2026] Top 20 AI Simulation Companies (2026) | https://flypix.ai/blog/top-ai-simulation-companies-2026/
[LinkedIn, retrieved 2026] Morteza Javid | LinkedIn | https://www.linkedin.com/in/morteza-javid-phd-p-eng-07205110/
[LinkedIn (LABonWEB page), June 2024] LABonWEB LinkedIn Post - Immigrant Entrepreneur Award | https://www.linkedin.com/feed/update/urn:li:activity:7077651016603072512
[Markets Insider, August 2024] The CanadianSME Small Business Awards 2023, proudly sponsored by Google, celebrated the achievements of Canada's finest small and medium-sized enterprises (SMEs) | https://markets.businessinsider.com/news/stocks/the-canadiansme-small-business-awards-2023-proudly-sponsored-by-google-celebrated-the-achievements-of-canada-s-finest-small-and-medium-sized-enterprises-smes-1033627378
[LinkedIn (Ali Rahimi), retrieved 2026] Ali Rahimi - Centre for Advanced Coating Technologies | LinkedIn | https://www.linkedin.com/in/alire/
[RocketReach, retrieved 2026] LABonWEB Information | https://rocketreach.co/labonweb-profile_b70557d9c50ff0ea
[Grand View Research, 2024] Engineering Simulation and Analysis Software Market Size, Share & Trends Analysis Report | URL not provided in structured facts.
[HolonIQ, 2024] Global Virtual Labs Market | URL not provided in structured facts.
[Gartner, 2024] Market Guide for AI in Engineering | URL not provided in structured facts.
[Crunchbase] Labster | URL not provided in structured facts.
[Crunchbase] Lab4U | URL not provided in structured facts.
[Crunchbase] Brilliant | URL not provided in structured facts.
Articles about Simavai
- Simavai's AI Simulation Platform Targets the Engineering Lab and the Classroom — The Toronto startup, backed by LabEight* Ventures, is building Forge AI for industrial R&D and LABonWEB for virtual learning.