Our work

Real results for real startups. Here's how we've helped teams build and secure their technology.

Fynnwell

Fynnwell was building cross-border payment infrastructure for Canadian SMBs, but their MVP couldn't handle the transaction volumes their first enterprise clients needed. The founding team had built a working prototype, but it was running on a single EC2 instance with no failover, processing times were unpredictable under load, and two large prospects had made SOC 2 a hard requirement before signing. With $12M in Series A funding and a 4-person engineering team in Toronto, they needed to move fast without breaking what was already working.

100x

Processing Capacity

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HealthTechSeed

Bexalyth

Bexalyth was building a remote physiotherapy platform in Vancouver — video consultations with motion-tracking wearable integration. Their 3-person team had built a working React Native app and a Node.js backend, but deployments were manual (SSH into a DigitalOcean droplet), there was no staging environment, and a botched deployment had caused 6 hours of downtime during a live patient session. With their seed round closing and BC Health Authority pilots starting in Q2, they couldn't afford another incident — but they also couldn't afford to stop building.

Northvex

Northvex, a Waterloo-based workflow automation platform for professional services firms, had grown to 400+ customers and $8M ARR — but their AWS infrastructure had been built reactively over 3 years and was showing its age. Cloud costs had tripled in 12 months to $85K/month with no clear explanation, their monolithic Rails application was hitting scaling limits during peak hours (Monday mornings when all their legal and accounting clients logged in simultaneously), and they'd failed a SOC 2 Type II audit due to overly permissive IAM roles and missing encryption on two data stores. Their VP of Engineering needed an outside team to untangle the technical debt without disrupting their 400 customers.

Keltrafy

Keltrafy had raised $4.2M to build a digital marketplace connecting Calgary commercial landlords with vetted contractors for building maintenance and energy retrofits. The two co-founders — both from commercial real estate — had strong industry relationships and a waitlist of 60 landlords, but no technical co-founder and no codebase. They'd been quoted 6+ months and $300K+ by agencies, and their investors were expecting a working product in 4 months to start generating revenue before their next raise.

Pyxwell

Pyxwell, an Austin-based community solar platform, had grown their subscriber base from 2,000 to 18,000 in 8 months after expanding to 3 new states. Their Django monolith and single-region AWS setup were buckling — page loads exceeded 8 seconds during enrollment periods, their Celery task queue was backing up by hours, and their 6-person engineering team was spending 60% of their time on firefighting instead of building the billing integration their utility partners needed. They'd tried to hire senior infrastructure engineers but couldn't compete with Austin's FAANG salaries.

1.2s

Page Load Time

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Logistics & Supply ChainSeries A

Velthari

Velthari was building an AI-powered freight matching platform in Amsterdam to connect European shippers with carriers across 12 countries. Their 5-person team had validated demand with a basic web portal, but they had no mobile presence — and 70% of their carrier base operated from phones on the road. Carriers were calling in to accept loads because the web app wasn't usable on mobile, costing Velthari 2 support reps and killing match speed. On top of that, their matching algorithm was a simple rules engine that couldn't account for route optimization, carrier reliability history, or real-time pricing fluctuations. With EUR 9M in Series A funding and contracts pending with three major Dutch logistics firms, they needed a native mobile experience for both platforms and an AI matching engine that could outperform manual dispatch — all within 5 months.

8x faster

Match Speed

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