I work at AwareAI, bouncing between Chiang Mai and Bangkok.
Working with cloud tech since 2009. Most recently spent a few years at AWS before jumping in with the Aware team. Studied Artificial Intelligence at university back when "AI" meant writing Prolog (yes, in 2000, before it was cool).
AwareAI delivers Agentic AI Cloud Solutions. Alongside that I ship a few things of my own, usually at the intersection of AI and whatever I happen to be riding.
Reach me: john@awareai.io · LinkedIn
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Lapfly AI-powered motorsport data analysis. Drop in a MoTeC, AiM, i2m, RaceChrono or GPS file and get a plain-English lap debrief, auto-detected braking markers, trail-braking depth, shift advice, delta-time, and public leaderboards. Built for riders, coaches, and race teams. |
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MudWatch Trail-condition forecasts for mountain bikers. Goes beyond "is it raining?" to model 3-day accumulated rainfall, surface type, trail grade, and drainage so you can pick the right trail for the day. Strava integration auto-annotates rides with conditions. |
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River Ping Flood Monitor Early-warning system for Chiang Mai, using the 6 to 8 hour flow time between upstream P.67 and downtown P.1 as a natural warning window. Combines live telemetry, Mae Ngat Dam release data, rainfall forecasts, and 220+ flood markers. A public-good project from AwareAI. |
Smaller open-source bits (CloudFormation snippets, ECR/Anchore tooling, Terraform modules) are pinned below.
A lot of what I build traces back to what I ride.
- Mountain biking: mostly downhill, the reason MudWatch exists
- Motorbike track racing: the reason Lapfly exists
- Road cycling: the weekly constant
- Former BMX and trials rider: old habits, still useful
- Former swimmer and Ironman triathlete (never again!)
