Web Summit Vancouver 2026: Enterprise AI Deployment Recap
Enterprise AI projects stalled as buyers demanded working systems. Clean tech competed on economics, not ESG. Vancouver surfaced constraint-driven founders.
Web Summit Vancouver returned for its second year as a test of whether the Pacific Northwest corridor could surface founders building for real deployment, not just venture narratives. With 20,000+ attendees and 1,500+ exhibiting startups, the event landed at a moment when tariffs were reshaping supply chains, AI adoption was stalling inside enterprises, and clean tech was being forced to compete on economics alone. Vancouver's position as a gateway to Asian markets and home to a $5 billion gaming industry made it a natural venue to assess which technologies were moving from prototype to production.
The 2026 edition revealed a sharp turn toward constraint-driven product development. Generative AI, once the dominant narrative, faced skepticism from enterprise buyers who had watched early projects fail to scale. Clean tech founders abandoned ESG positioning in favor of cost and speed arguments. The pitch competition winner, CURA Climate, signaled the shift: climate solutions now compete on commercial viability, not impact storytelling. The thesis is clear—buyers are done funding experiments.
81.5% of founders now use AI for content. 58.7% say it doesn't sound like them.
They surveyed 92 founders to find out why — and what the ones who've cracked it are doing differently. Free report, no gate.
What Stood Out
The founder and investor mix reflected a market demanding proof of deployment, not just technical capability.
- Enterprise AI founders were defending stalled pilots, not celebrating launches. Buyers wanted systems that worked without constant tuning, and most early AI projects had failed to move beyond proof-of-concept.
- Clean tech startups positioned on cost and speed, not sustainability. With anti-ESG sentiment rising and fuel prices surging, founders competed on economics—renewable energy and battery storage now outperform fossil fuels on deployment timelines.
- Cross-border fintech and SaaS founders treated tariffs as a product constraint, not a policy problem. Supply chain disruption forced startups to build for fragmented markets and sovereign deployment from day one.
- Gaming and film tech startups merged real-time AI with production workflows. Studios were testing AI actors and adaptive storyworlds, but the focus was on cost reduction and speed, not creative experimentation.
- CURA Climate's pitch win validated commercialization over impact narratives. The climate tech winner succeeded by proving market fit, not by leading with environmental outcomes.
PITCH Competition
Web Summit Vancouver's pitch competition cut across climate, AI infrastructure, health, and construction. The winner signaled where the market is heading.
Winner: CURA Climate
Founder: Sabrina Scott
Pitch:
CURA Climate uses electrochemical technology to split limestone into lime and pure CO₂ with electricity instead of heat, enabling cement manufacturers to produce Ordinary Portland Cement while reducing emissions by up to 85%.
Problem:
Cement production generates 8% of global CO₂ emissions, primarily from the chemical reaction that creates clinker, and decarbonizing typically requires new infrastructure or feedstocks that disrupt supply chains.
What stood out:
The system retrofits into existing plants as a drop-in replacement for the precalciner, eliminating the need for costly new supply chains or greenfield builds while using 45% less energy than plants with carbon capture.
Traction:
Secured $2.1M in pre-seed funding and $900K in non-dilutive grants, signed MOUs with TITAN Group and multiple construction firms, and received letters of support from Heidelberg Materials and Amrize.
Why it matters:
By retrofitting into existing facilities and preserving current feedstocks, CURA removes the capital barrier that has prevented cement producers from decarbonizing at scale.
Standout PITCH Startups
Below is a closer look at the startups that stood out across the broader cohort.
Astron Health
Founder: Ben Whately
Pitch:
Astron Health integrates genomic, transcriptomic, and proteomic data to identify which cancer pathways are actively driving each patient's tumor, then ranks existing drugs most likely to work against those targets.
Problem:
Seventy percent of precision cancer therapies fail because treatment matching relies on DNA mutations alone, ignoring whether those mutations are actually expressed and active in the patient's tumor.
What stood out:
The platform identifies mutations flagged by genomic tests that aren't expressed at the RNA level—meaning the drug has no target to bind—and catches active pathways that single-gene tests miss entirely.
Traction:
The company has delivered over 170 reports and generated £600k in revenue across 500+ patients through 19 clinical partners in the UK and US.
Why it matters:
By filtering out non-responders before treatment starts, Astron turns precision oncology from a 30% success rate into a system that avoids wasted spend and months of ineffective, toxic therapy.
Bizby
Founder: Marty Cerisano
Pitch:
Bizby is a Canadian-hosted freeform whiteboard platform built for enterprise collaboration, offering real-time co-editing and AI-assisted facilitation.
Problem:
Canadian public sector and regulated organizations face procurement restrictions that block US-headquartered collaboration tools, leaving no enterprise-scale alternative for infinite-canvas whiteboarding.
What stood out:
Bizby is the only freeform whiteboard platform built end-to-end in Canada at enterprise scale, positioning it as a direct replacement rather than a workaround in a market where procurement policy now determines vendor eligibility.
Traction:
Nine paying teams are in production across federal, provincial, and healthcare sectors, including Immigration and Refugee Board of Canada and Transport Canada.
Why it matters:
As Canadian procurement rules tighten around vendor nationality, Bizby offers regulated organizations a compliant path to maintain collaborative workflows without reverting to static tools or unsanctioned software.
Butterfly Legal
Founder: Matt Canzer
Pitch:
Butterfly Legal uses an AI assistant called Bella to guide self-represented litigants through BC Small Claims Court—organizing their case, drafting documents, and managing deadlines—then connects them with licensed lawyers inside the platform for targeted advice.
Problem:
Most people facing routine legal disputes can't afford a lawyer but lack the guidance to navigate court processes properly on their own.
What stood out:
The platform separates legal information (provided by AI) from legal advice (provided by lawyers), allowing users to complete most of the work themselves while ensuring compliance with unauthorized practice of law regulations.
Traction:
The founder has personally helped 80+ self-represented litigants through small claims disputes, and the company jointly won a $10K pitch competition at Web Summit Vancouver.
Why it matters:
By making legal guidance affordable and accessible at scale, Butterfly Legal addresses a market where three in four North Americans with a legal problem never get professional help.
Chamber
Founder: Charles Ding
Pitch:
Chamber provides an autonomous AIOps agent that manages and optimizes GPU infrastructure across multi-cloud and on-prem environments, automating workload orchestration, performance debugging, and resource balancing for machine learning teams.
Problem:
Machine learning teams spend excessive time manually debugging workload failures and managing fragmented GPU clusters, leading to idle GPUs in one environment while jobs queue in another.
What stood out:
The platform uses autonomous agents that self-learn to maximize workload efficiency, shifting infrastructure management from manual intervention to automated optimization that adapts in real time.
Traction:
The company has 7 paid pilots totaling $40k and $250k ARR on conversion, including one Global Fortune 1000 customer.
Why it matters:
As GPU utilization rates fall below 50% across the industry, automating infrastructure orchestration directly addresses the bottleneck between acquiring compute and efficiently using it at scale.
ConnectLoop
Founder: Atif Muhammad
Pitch:
ConnectLoop deploys AI agents on business websites to engage visitors, qualify leads, book meetings, and push structured data into CRMs—operating 24/7 across chat, email, and SMS.
Problem:
Most website traffic never converts into pipeline because visitors leave without engaging, response delays kill intent, and follow-up is inconsistent.
What stood out:
ConnectLoop connects the full workflow from conversation to CRM sync—capturing intent, scoring leads, routing by availability, and triggering follow-ups—rather than stopping at chat or form collection.
Traction:
The company has 100+ customers and is growing quickly.
Why it matters:
By turning static websites into active sales infrastructure, ConnectLoop addresses the gap between traffic acquisition and pipeline conversion—especially outside business hours.
DRIVE Hockey Analytics
Founder: Mike Dahlstedt
Pitch:
DRIVE Hockey Analytics installs sensor-based tracking systems in amateur hockey arenas to measure fitness, performance, and tactical game data, generating AI-powered performance reports benchmarked against peers.
Problem:
Amateur players lack objective guidance on how to improve, relying on inconsistent coaching advice or paying thousands for elite development programs.
What stood out:
The company built a patented sensor infrastructure that captures tactical and biomechanical data video systems miss, creating a dataset of over 800 million rows that powers increasingly accurate player development insights.
Traction:
The company has run 20 paid pilots generating approximately $1M in revenue, tracked 7,500 players, and signed a deployment agreement with Canlan, which operates 47 arenas serving 50,000 members.
Why it matters:
By making professional-grade performance tracking affordable at scale, DRIVE shifts amateur hockey evaluation from subjective observation to data-driven development accessible to any player.
eSense Health
Founder: Elayne Wandler
Pitch:
eSense Health delivers a self-guided digital platform using Cognitive Behavioral Therapy and Mindfulness-Based Therapy to treat women's sexual desire and arousal disorders.
Problem:
Over 40% of women experience sexual difficulties, but fewer than 20% seek help due to stigma, limited access to specialists, and high costs.
What stood out:
eSense is the first digital therapeutic in this category backed by a randomized controlled trial showing outcomes comparable to in-person therapy—87% of users reported higher sexual desire and 77% reported less sex-related distress.
Traction:
The company has initiated a commercial pilot with approximately 300 paid users, a waitlist of over 1,100 individuals, and interest from more than 300 referral clinics.
Why it matters:
By digitizing gold-standard therapy for a condition that affects millions but remains largely untreated, eSense creates a scalable pathway to care in a market historically defined by inaccessibility and clinical dismissal.
InPower
Founder: Razan Talebian
Pitch:
InPower is a social platform where users practice healthier behavioral patterns daily through expert-led education, AI-supported reflection, moderated communities, and restorative accountability systems.
Problem:
Social media amplifies conflict and reactive behavior without providing structured support for users to develop emotional and social skills.
What stood out:
Rather than moderating harm after it occurs, InPower intervenes in real time—guiding users toward constructive responses through daily check-ins, reflection prompts, and restorative pathways that prioritize growth over punishment.
Traction:
The platform has grown to 26,000+ community members, established relationships with 22+ universities, and been selected for Web Summit Vancouver's PITCH competition.
Why it matters:
If behavioral skills can be practiced and reinforced continuously rather than taught episodically, platforms could shift from reactive moderation to proactive culture-building at scale.
LimitlessAI
Founder: Matthew Dillon
Pitch:
LimitlessAI is a self-improving conversation platform that handles customer interactions across channels for service businesses. The platform captures demand from unanswered calls and extracts actionable signals from conversations to drive revenue.
Problem:
Service businesses lose revenue when they miss high-intent calls or fail to act on what customers reveal during conversations.
What stood out:
The platform combines conversational data across all channels into a self-improving loop, meaning each interaction makes the system smarter at routing, responding, and identifying what closes deals.
Traction:
The company has 15 paying customers generating $4,000 in monthly recurring revenue, plus 4 channel partners. One customer attributed $400,000 in sales within 90 days with a double-digit closing rate and 15% conversion lift.
Why it matters:
As customer expectations shift toward immediate, 24/7 response, businesses that can capture and learn from every conversation gain a compounding advantage in converting demand.
MindArch Health
Founder: Nadine Wilches
Pitch:
MindArch Health uses machine learning trained on longitudinal data to predict mental health risk trajectories at the population level and automate preventive intervention plans before symptoms emerge.
Problem:
Schools and healthcare systems spend $200 billion annually on avoidable behavioral health crises because they lack tools to identify vulnerabilities before symptoms appear.
What stood out:
The platform identifies institutional risk patterns using proprietary models that predict who is most at risk and why, shifting the intervention point years earlier than traditional reactive approaches.
Traction:
The company has converted 100% of pilots to paid customers across 7 institutions in education and healthcare, generating early revenue.
Why it matters:
Moving mental health intervention upstream from crisis response to population-level prevention reduces institutional costs while addressing chronic stress before it requires clinical treatment.
REearthable
Founder: Charlotte Wintermann
Pitch:
REearthable develops ecoPLAS®, a biodegradable plastic alternative made from CO₂-captured limestone that replaces polypropylene in packaging. The material runs on existing injection molding equipment without requiring manufacturers to retool their production lines.
Problem:
Small-format plastics used in beauty and cosmetics are structurally unrecyclable and contribute to the ~5 grams of microplastics people ingest weekly.
What stood out:
ecoPLAS® functions as a drop-in replacement that matches polypropylene's performance while eliminating microplastics and reducing CO₂ emissions by 38% per pound produced.
Traction:
The company has secured a utility patent, achieved compliance with 28+ global standards, proven manufacturing in injection molding, and is conducting beauty brand pilots.
Why it matters:
As $39B in consumer spending shifts toward sustainable packaging and regulations tighten, materials that integrate into existing infrastructure provide a scalable decarbonization path without forcing manufacturers to rebuild their operations.
Swell
Founder: Huan Ho
Pitch:
Swell builds AI agents that automate post-sales operations for customer success teams by creating a unified customer knowledge graph from CRM data, product usage, support tickets, and communications.
Problem:
Customer success teams waste time on manual work across fragmented tools, making it difficult to maintain account context or identify churn and expansion signals.
What stood out:
Swell connects people, products, decisions, and customer history into a single graph, shifting post-sales from reactive firefighting to proactive account management.
Traction:
Early stage. No public metrics yet.
Why it matters:
With 80% of future revenue tied to existing customers and 67% of churn preventable, automating post-sales intelligence allows companies to scale retention and expansion without proportionally scaling headcount.
Synexiom Labs
Founder: Meghraj Solanki
Pitch:
Synexiom Labs builds a patented, model-agnostic reasoning layer that sits on top of any foundation model, forcing it to reflect before responding, surface contradictions, and articulate uncertainty.
Problem:
In natural resources, energy, healthcare, and government, confident hallucination creates liability where decisions carry real consequences.
What stood out:
The company treats epistemic humility as an architectural property rather than a prompt or fine-tune—building honesty into the system instead of correcting for overconfidence after the fact.
Traction:
Cortexiom is live in market with tiered pricing, and the company is self-sustaining through commercial revenue from custom AI engagements and product subscriptions.
Why it matters:
If reasoning becomes infrastructure rather than application logic, organizations can deploy trustworthy AI without rebuilding systems every time a foundation model changes.
Teacher Time Machine
Founder: Sharon Skretting
Pitch:
Teacher Time Machine is an instructional design platform that helps educators create curriculum-aligned learning materials customized to local context and student needs using backward design principles.
Problem:
Nearly half of teachers leave the profession within five years, driven by burnout from excessive planning workloads and generic tools that ignore teacher expertise.
What stood out:
The platform embeds a worldview lens structure that allows teachers to customize curriculum delivery while maintaining pedagogical rigor, positioning teacher judgment at the center rather than replacing it with automation.
Traction:
The company relaunched its platform in 2025, now works with eight Alberta school districts, reached $100K in revenue, has 6,800 users, and won the Alberta AsTech Award for Regional Software Innovation.
Why it matters:
Tools that preserve teacher agency while reducing administrative burden address both retention and instructional quality in a profession facing unsustainable attrition rates.
Vraust
Founder: Elnathan Tiokou
Pitch:
Vraust detects and blocks online, phone, and email scams in real time before users send money or share sensitive information.
Problem:
Consumers realize they've been scammed only after transferring funds or compromising personal data.
What stood out:
Vraust intervenes during the transaction itself, stopping the scam at the moment of risk rather than relying on post-incident reporting or user awareness.
Traction:
The company is running pilots with banks and law enforcement agencies and has over 50 active users on the platform.
Why it matters:
Real-time interception shifts fraud prevention from reactive investigation to proactive consumer protection, addressing a gap as scam sophistication outpaces user education.
Arkivist
Founder: Robert Perry
Pitch:
Arkivist builds a chain-of-custody layer for AI decisions, logging and anchoring every output to create court-admissible audit trails for enterprise AI deployments.
Problem:
Enterprises deploying AI cannot defend how models reached specific decisions when regulators, boards, or courts demand proof of reliability.
What stood out:
The platform decomposes AI outputs into verifiable claims and anchors them to a public ledger, treating AI decisions like forensic evidence rather than black-box predictions.
Traction:
The system has anchored 1.3 million claims and achieved 99.8% accuracy in a public chess demonstration on Hedera's testnet.
Why it matters:
As AI moves into regulated industries, the ability to prove decision provenance becomes a compliance requirement, not a feature.
AssisTech SmartShower
Founder: Sasha Ovalle
Pitch:
AssisTech SmartShower develops a voice-controlled, Alexa-enabled showerhead accessory that installs in under five minutes and allows users to start, adjust, and stop showers without physical touch.
Problem:
Elderly, disabled, and mobility-impaired individuals often cannot safely reach or turn standard shower controls, forcing reliance on caregivers and increasing fall risk.
What stood out:
Rather than requiring costly bathroom renovations, the device retrofits existing showers as an accessory, making voice control accessible without infrastructure changes.
Traction:
The company won the 2025 PDMA Global Student Innovation Challenge and was named a 2025 Most Disruptive Business School Startup by Poets&Quants.
Why it matters:
By adapting mainstream smart home technology to assistive health needs, AssisTech demonstrates how consumer voice AI can restore autonomy in essential daily routines for mobility-impaired users.
Atlas Primer
Founder: Hinrik Atlason
Pitch:
Atlas Primer converts documents and training materials into interactive, conversational audio courses that function like an AI-powered podcast, enabling hands-free learning.
Problem:
Traditional corporate training is screen-bound and text-heavy, creating barriers for busy professionals and neurodivergent learners who need more flexible formats.
What stood out:
The platform shifts learning from passive reading to active conversation, making upskilling accessible on-the-go without requiring visual attention or dedicated screen time.
Traction:
Named Educational Startup of the Year 2026, accepted into Google for Startups Cloud Program, and selected to compete at Web Summit Vancouver 2026.
Why it matters:
Conversational audio learning removes friction from professional development, making continuous upskilling practical for distributed teams and time-constrained workers.
Blue Dot Motorworks
Founder: Tom Gurski
Pitch:
Blue Dot Motorworks produces universal, bolt-on retrofit kits that convert gas and diesel vehicles into plug-in hybrids, providing 35–50 miles of electric range while retaining the internal combustion engine.
Problem:
Fleet operators face pressure to reduce emissions but cannot afford $60,000+ electric vehicles or the depot charging infrastructure that can take over a year to install.
What stood out:
The vehicle-agnostic architecture enables mass production and one-day installation by third-party shops, breaking the cost and scalability constraints that have kept EV conversions a bespoke, multi-year-waitlist business.
Traction:
The company has developed functional prototypes validated in real-world use and secured letters of intent for pilot programs from fleet operators.
Why it matters:
Retrofitting existing fleets offers a faster path to cutting transportation emissions without waiting for the decades-long vehicle turnover cycle or relying on constrained battery supply chains.
ClassClown
Founder: Joshua Ekundayo
Pitch:
ClassClown built Hey Cleo, a voice-based platform where students explain their thinking out loud while completing assignments. The system guides reasoning in real time and adjusts prompts based on understanding and emotional state.
Problem:
Students get stuck during independent work but receive little guidance when they struggle.
What stood out:
Voice interactions capture proof of understanding rather than polished answers, giving educators qualitative insight into reasoning, misconceptions, and confidence levels instead of binary correctness.
Traction:
The company reports $470K ARR, 300+ active students, and a 74% assignment completion rate.
Why it matters:
Requiring students to verbalize their process shifts assessment from answer validation to reasoning verification, making it harder to bypass understanding with generated solutions.
DealStack.ai
Founder: Alex Hines
Pitch:
DealStack.ai aggregates business listings and uses AI to analyze financial documents for acquisition entrepreneurs searching for companies to buy.
Problem:
Buyers spend months manually filtering leads across fragmented platforms and reviewing dense financial documents to find viable acquisition targets.
What stood out:
The platform automates initial due diligence by extracting and standardizing data from CIMs, turning what's typically a weeks-long manual review into a structured analysis that helps buyers evaluate deals faster and present themselves more credibly to brokers.
Traction:
The platform aggregates over 100,000 active business listings and reports usage by thousands of acquisition entrepreneurs.
Why it matters:
As retiring business owners create a surge in available SMBs, independent buyers need infrastructure that lets them compete at the scale and speed previously reserved for institutional acquirers.
Eclatira
Founder: Maryam Gilsenan
Pitch:
Eclatira builds multimodal AI agents that combine voice, real-time vision, and backend task execution to automate front-desk and customer support operations across hospitality, retail, and healthcare.
Problem:
Current AI tools can handle conversation but cannot process visual inputs like ID verification or damage assessment, forcing businesses to rely on human follow-up for tasks requiring sight.
What stood out:
The platform treats vision as a core input rather than an add-on, allowing agents to operate autonomously in workflows that require both conversation and real-time visual processing—eliminating the handoff between AI and human staff.
Traction:
The company has deployed agents for medication pickup workflows, administrative operations across 1,300+ hotels, and customer service for a Shopify store with millions in revenue.
Why it matters:
Automating tasks that require both sight and speech removes a structural bottleneck in industries where visual verification has kept human labor locked into otherwise automatable roles.
GeneGenius
Founder: Zuhra Maksudi
Pitch:
GeneGenius is an AI-powered genomic interpretation platform that processes VCF files into clinician-ready reports in under four minutes, synthesizing population data, clinical literature, and ACMG criteria to classify variants for rare disease diagnosis, oncology, and pharmacogenomics.
Problem:
Clinicians spend 6–8 hours per genome manually reviewing literature and clinical context, creating multi-week turnaround times despite fast sequencing.
What stood out:
The platform automates the entire interpretation workflow—from annotation through classification to report generation—replacing a fragmented, manual process that typically requires expert review at every stage.
Traction:
The company has 200+ daily researchers using the platform with 8.4 analyses per user and two signed letters of intent from academic institutions.
Why it matters:
By compressing interpretation from weeks to minutes, the approach enables labs to scale genomic diagnostics without proportionally expanding scarce geneticist headcount.
goNEON
Founder: Raphael Eder
Pitch:
goNEON builds agentic AI software that generates regulation-compliant infrastructure and mobility plans in minutes, automating design and simulation for road, utility, and transit projects.
Problem:
Urban planning and infrastructure design typically take months or years to navigate local regulations and produce viable plans.
What stood out:
The platform handles regulatory compliance as part of the design process itself, removing a major bottleneck that traditionally requires manual legal and technical review at every iteration.
Traction:
The company secured CHF 40,000 in Venture Kick Stage II funding and launched pilots with İSBAK, Okan University, and Transport for West Midlands.
Why it matters:
Automating compliance within infrastructure design allows municipalities to move from concept to execution faster, addressing delays that slow smart city development.
Neon Compliant
Founder: Sarah Hillifer
Pitch:
Neon Compliant converts customer postal codes into detailed personality and lifestyle profiles, helping marketers visualize their audience and identify look-alike customers across Canada.
Problem:
High-quality demographic and lifestyle data is typically too expensive and complex for small-to-medium enterprises and small charities to access.
What stood out:
The platform makes consumer insight tools—previously reserved for enterprises with large budgets—accessible to smaller organizations that lack dedicated data teams or analytics infrastructure.
Traction:
Selected as one of 35 startups pitching at Web Summit Vancouver 2026, accepted into the Web Summit Startup Readiness Engine, and named a Round 2 Finalist in the 2026 New Ventures BC Competition.
Why it matters:
Smaller brands and nonprofits can now execute targeted, data-driven campaigns without enterprise-level resources.
PaiBox
Founder: Sherry Li
Pitch:
PaiBox automates property maintenance and repair workflows by coordinating tenants, property managers, and service vendors through an AI-driven execution layer.
Problem:
Property managers spend most of their time manually coordinating vendors and chasing updates rather than managing properties or scaling operations.
What stood out:
PaiBox doesn't just track work orders—it actively dispatches, coordinates, and completes jobs by controlling the workflow between property management systems and vendor networks.
Traction:
The company is onboarding 5,000+ units, generating $2K/month in revenue from paid customers, and reports a 90%+ demo-to-pilot conversion rate.
Why it matters:
By automating the nonlinear workflows that consume most of property management time, PaiBox enables real estate operators to scale without proportionally increasing coordination overhead.
Panoptica Technologies
Founder: Martin So
Pitch:
Panoptica Technologies builds Watchtower, an AI-powered tactical intelligence platform that automates open-source intelligence collection and analysis to identify emerging threats and predict enemy courses of action in irregular warfare environments.
Problem:
Military and intelligence analysts are overwhelmed by data volume and rapid deception tactics, forcing commanders to make critical decisions with incomplete information.
What stood out:
The platform combines operator-sourced ground truth data from ex-special forces contractors with algorithms designed to detect deception in sparse data environments, focusing specifically on irregular threats in Latin America where adversaries actively weaponize misinformation.
Traction:
Panoptica graduated from Georgia Tech's CREATE-X incubator, signed a distribution agreement with Carahsoft, filed a patent, and was accepted into the Rice Business Plan Competition.
Why it matters:
Automating tactical intelligence collection allows defense agencies to shift analyst focus from manual data processing to strategic decision-making in environments where misinformation is weaponized.
Pricing For Profit
Founder: Katy Baker
Pitch:
Pricing For Profit offers a self-serve app that guides business owners through calculating their unit economics—including capacity for billable work, all business costs, debt recovery, and desired profit margins—to generate profitable pricing models and operational plans.
Problem:
Many small business owners lack financial literacy and struggle to understand their true costs, resulting in chronic underpricing despite high activity.
What stood out:
The app surfaces hidden costs across 47+ categories and factors in utilization reality—the gap between theoretical capacity and actual billable hours—which competitors often miss.
Traction:
The company has served 200+ paid clients, with users reporting average price increases of 55% to 90% and income growth of 1.5x to 2x.
Why it matters:
By making unit economics accessible without hiring a CFO, the platform addresses a structural gap that causes nearly half of small businesses to fail within five years.
Reach Machine
Founder: Narendran Asokan
Pitch:
Reach Machine uses AI to predict which Instagram reels will go viral by analyzing engagement signals in a 24-48 hour window before the algorithm amplifies distribution.
Problem:
Marketers spend 12-15 hours per week manually scrolling competitor feeds with no structured way to detect breakout content before trends peak.
What stood out:
The system identifies reels showing strong engagement signals before Instagram's distribution catches up, giving creators a 24-48 hour advantage to replicate patterns while they're still emerging.
Traction:
Product 90% complete with 936 backend tests deployed on AWS. A 30-day pilot with 15-20 design partners launched in March 2026.
Why it matters:
If viral prediction becomes reliable at scale, independent creators gain enterprise-level analytical capabilities without waiting until trends have already peaked.
REPWR
Founder: Zachary McCue
Pitch:
REPWR designs modular solar energy systems that convert intermodal freight vehicles—container ships, trains, and commercial trucks—into mobile power stations, displacing diesel fuel for onboard hotel loads and auxiliary power.
Problem:
Heavy transport operators spend billions annually on diesel fuel, maintenance, and carbon penalties to power non-propulsion systems while vessels and vehicles are in operation or at berth.
What stood out:
The system integrates without requiring recalculation of vessel stability or new inclining tests, enabling drop-in deployment across existing fleets with no structural redesign.
Traction:
REPWR is piloting modules with Lomar Shipping on a pathway to 20+ vessels in 2026, has deployed units at Los Angeles trucking depots, and projects $5 million in revenue by 2027.
Why it matters:
REPWR offers shipping and logistics operators an immediate, modular alternative to diesel that cuts fuel costs and emissions without waiting for hydrogen or methanol infrastructure to mature.
ScopeDocs.ai
Founder: Vivian Lin
Pitch:
ScopeDocs generates automated, source-linked documentation for engineering teams by integrating with GitHub, Slack, Linear, and Supabase.
Problem:
Engineering documentation becomes outdated quickly, forcing developers to search across disconnected platforms for context.
What stood out:
The documentation stays verifiable by linking directly to source code and tools, which removes the manual maintenance burden that typically causes knowledge bases to decay.
Traction:
Won 2nd place at the Seattle Startup Summit 2026 out of 120 early-stage AI startups.
Why it matters:
Automated, source-linked documentation reduces onboarding time and context-switching as engineering toolchains fragment across more platforms.
Strathwell
Founder: Moosa Zaidi
Pitch:
Strathwell converts event spaces into execution-ready blueprints by mapping layouts, services, budgets, timelines, and risks through an AI-powered platform.
Problem:
Event teams struggle to align logistical, financial, and spatial elements across fragmented tools, slowing approvals and execution.
What stood out:
The platform automates the blueprinting process that typically requires manual coordination across multiple stakeholders, turning spatial and operational data into a unified execution plan that reduces planning friction.
Traction:
Selected to attend Web Summit Vancouver 2026; founder Moosa Zaidi named an EY Entrepreneur Of The Year 2026 finalist and Forbes 30 Under 30 honoree.
Why it matters:
Automating event blueprinting shifts planning from reactive coordination to proactive execution, allowing venues and production teams to operate with greater precision under tighter timelines.
Workbench
Founder: Umer Kazi
Pitch:
Workbench builds autonomous AI agents that automate back-office workflows for construction companies, including job costing, billing, forecasting, and compliance. The agents integrate with existing construction software and propose actions via SMS or messaging platforms for human approval.
Problem:
Mid-market construction contractors lose 5-6% of profit margins to back-office inefficiencies caused by miscoded costs, delayed reporting, and compliance gaps from disconnected data.
What stood out:
Rather than replacing existing systems, Workbench positions its agents as "crew members" that work across disconnected tools and surface decisions where contractors already communicate, reducing the friction of adoption.
Traction:
The company is working with construction firms including Duron, GIP, Lavish, One Developers, Blue Avenue Developments, and Saima Group.
Why it matters:
Construction's labor shortage makes it difficult to scale administrative teams, so automating repetitive tasks protects margins without adding headcount.
Deployment as the New Filter
The cohort that surfaced in Vancouver reflects a market that has stopped rewarding technical novelty and started punishing deployment failure. Enterprise AI stalled because buyers refused to fund another round of pilots that never shipped. Clean tech survived by competing on cost, not carbon credits. Founders who treated tariffs and fragmented markets as design constraints—not obstacles—built systems that could actually deploy.
This is not a pivot. It is a correction. The startups that will define the next cycle are the ones building for the constraints that killed their predecessors: buyer skepticism, regulatory fragmentation, and the requirement that systems work without constant intervention. Vancouver showed which founders understood that commercialization is not what happens after product-market fit—it is the product.
We will continue tracking the founders and systems shaping what is UpNext in the global economy.
