Director – Corporate Finance

Torquen vs Strava: which app shares Your Motorcycle ride stats best? If you record your rides, sooner or later you want to show them off - the route, the distance, the numbers, turned into something worth posting. A lot of riders reach for Strava by default, because it's familiar and the tracking is solid. But Strava was built for runners and cyclists, and it shows most clearly in how it gets your ride from "recorded" to "posted." Here's an honest look at how Strava handles ride sharing, where it falls short for motorcyclists, and how a sharing-first rider app like Torquen approaches the same job. Quick verdict. * Strava - a brilliant, mature tracker, but fitness-first. Its stats-sharing works, yet the workflow is clunky and the styling has frustrated users. It tracks your ride fine; it just doesn't speak motorcycle. * Torquen - built sharing- and community-first for riders. One-tap, auto-generated Story stickers and a private-crew social model. Younger and Australian-built, with a narrower feature set than Strava's years of polish. Now the detail. Strava: great tracker, awkward share. Strava is the default activity app for millions, and plenty of motorcyclists use it because it's familiar and the GPS tracking is rock solid. Its Stats Stickers feature lets you overlay activity stats - distance, time, pace - onto any photo inside an Instagram Story. The catch is the workflow. To get a clean result you open the activity, hit share, scroll through transparent stat templates, choose Copy to Clipboard, switch to Instagram, start a Story with your photo, tap as if adding text, and paste. The direct "share to Story" shortcut exists but doesn't let you reposition the stats over your image. It's a multi-step shuffle - and when Strava reworked its default template, users pushed back that the stats had become oversized and were covering their photos, to the point that third-party tools sprang up purely to generate cleaner overlays. Then there's the deeper mismatch: Strava is a fitness app. It thinks in pace, heart rate and segments. A motorcycle ride isn't a workout, and the stats, leaderboards and framing are all built for athletes. It records your ride accurately; it just frames it as exercise. Best for: riders already deep in the Strava ecosystem who want solid tracking and don't mind the manual share dance. Torquen: built to be shared. Torquen comes at the problem from the opposite end. Where Strava is fitness-first, Torquen is sharing- and community-first - designed for riders who want their rides to look good and their riding to be social. The flagship feature is the ride sticker. Every ride you record automatically generates a 1080x1920 Instagram Story sticker - your route drawn as a clean polyline over a six-tile stat grid, with a gradient wash baked in so the text stays legible over any background photo - and hands it straight to Instagram Stories. No copy-to-clipboard, no third-party overlay app, no oversized template stamped across your shot. Record, tap, post. (The full workflow is in How to Share Your Motorcycle Rides on Instagram.) Around that sits a rider-social model built on real relationships rather than a public directory: invite-only private crews, locality-based ride and event discovery, a garage and service log for your bikes, and a learner-rider mentorship feature. The social funnel runs public ride | human connection | private crew - a deliberately different shape from the public-feed-and-leaderboard model. On the practical side: it tracks via GPS through screen-lock, offers Pro features like snap-to-roads cleanup and GPX export, and is metric-first and built around Australian roads and conditions to start, with Pro priced at $2.99/month (AUD). The honest caveats: Torquen is the newcomer. It doesn't have Strava's years of polish, scale or breadth of integrations, and it isn't a dedicated navigation tool - if turn-by-turn routing and offline map planning are your priority, a purpose-built navigation app will serve you better. What Torquen is built to do is make every ride share-ready and turn your riding into a community. Best for: riders who post their rides, run with a regular crew, and want sharing to be one tap instead of a workaround. Side by side. | / | Strava | Torquen | | Built for | Fitness tracking | Rider social + sharing | | One-tap ride sticker | No (manual copy/paste) | Yes (auto-generated) | | Story styling | Fixed template, criticised | Custom, gradient-washed, Pro unbranded | | Social model | Public feed, segments, leaderboards | Private invite-only crews | | GPX export | Pro | Pro | | Garage / service log | No | Yes | | Motorcycle-specific | No | Yes | | Pro price | Varies | $2.99/mo AUD | How to choose. It comes down to what you actually do after a ride: * You're already on Strava and just want clean tracking | stick with Strava, and live with the share workflow. * You navigate and plan serious multi-day trips | a dedicated motorcycle navigation app will out-plan both - sharing isn't the job there. * You post your rides and ride with a crew | Torquen, because that's the entire point of it. Plenty of riders run more than one app - one to plan and navigate, another to share and stay connected with their crew. They're not really solving the same problem, and they're not mutually exclusive. For the deeper "why sharing matters" angle - including the 2026 engagement data that explains why one-tap Story sharing is worth caring about - see the Motorcycle Influencer's Playbook. Comparison reflects publicly available information as of 2026; features and pricing change, so check current app listings before subscribing. Torquen is an independent Australian-built motorcycle riding app.

Strava now lets subscribers analyze training data with Claude AI. Introducing the Garmin rumors try-on lab. * June 1, 2026 * 9:52 pm EDT * Billy Grenis Strava is launching a new MCP Connector that gives subscribers a way to connect their Strava training history directly to Claude, Anthropic's AI assistant. Strava announced the new MCP Connector on June 1, giving subscribers a way to ask natural-language questions about their own activity data through Claude. The feature is beginning to roll out globally and is included with Strava subscriptions. That may sound technical, but the idea is fairly simple: instead of exporting your Strava data, uploading files, or manually copying workouts into an AI chatbot, the MCP Connector lets Claude securely read your Strava data and answer questions based on your actual training history. What is MCP? MCP stands for Model Context Protocol. In plain English, it is a way for an AI assistant to connect to an outside app or data source in a structured way. In this case, Strava is the data source and Claude is the AI assistant. Once connected, Claude can review your Strava activity history and use it to answer questions about your training. That could include things like weekly mileage, pace trends, heart rate patterns, cycling power, training load, activity history, gear usage, and cross-training. Strava says the connector can access live Strava data rather than relying on a one-time static export. What you can ask it. You can ask questions about their activities and health in normal language. For example, a runner could ask whether their easy runs are actually easy enough, how their mileage has changed in the lead-up to recent races, or whether their long runs are trending in the right direction. A cyclist could ask how power has changed over time, whether a specific block of training has improved performance, or how different types of rides affect fitness. Someone who mixes running, cycling, strength training, and other activities could ask how cross-training is affecting their overall progress. Strava already has a lot of data, but most users do not have an easy way to interrogate that data beyond the charts and features Strava chooses to show inside the app. This gives subscribers a more flexible way to ask their own questions. What Strava data can it use? Strava says the MCP Connector can provide access to detailed activity data, including per-second stream data such as heart rate and pace, GPS data for geographic analysis, cycling power data, and club and event data. Strava's support page also says the connector can currently be used for activity history, fitness trends, readiness, goal planning, cross-sport analysis, and gear. How it works. The Strava MCP Connector is available through Claude. Strava says users connect their accounts through OAuth, which is the same general authorization flow used by many third-party app connections. Connection instructions here. Once connected, subscribers can access the Strava MCP Connector through Claude.ai, Claude's desktop experience, or Claude Code. Strava says it is launching first with Anthropic's Claude and is looking to support other AI clients in the future. The connector is read-only, which means Claude can analyze Strava data but cannot upload, edit, or delete activities. Strava also says access can be revoked from Strava settings. What this means for fitness data. Fitness data is becoming easier to use outside of the app where it was originally collected. Most fitness platforms already analyze your data in some way. Garmin Connect, Strava, Apple Fitness, Whoop, Oura, and others all have their own dashboards, charts, summaries, and insights (some of which leverage AI already). But those insights usually live inside each company's own app. By connecting Strava data to Claude, users may be able to put their training history in the context of other things they already use Claude for, including broader health questions, personal goals, race planning, lifestyle context, nutrition, recovery, scheduling, or other personal information they choose to share with the AI assistant. For example, a runner could ask whether their mileage buildup looks aggressive given their recent sleep, stress, travel, or injury history. A cyclist could ask how their power trends compare with a specific training block. Someone training across multiple sports could ask how running, cycling, strength work, and recovery are fitting together. The bottom line. Strava's MCP Connector gives subscribers a new way to analyze their training history through Claude. It is read-only, limited to Claude at launch, and only available to Strava subscribers. It also does not make Claude a perfect coach. AI-generated training advice can still be wrong, incomplete, or missing important context. For Garmin users, the most interesting part may be that Garmin's own analysis still lives in Garmin Connect (and requires a Connect+ subscription), while Strava's MCP Connector could let athletes bring synced Garmin workout data into a broader AI conversation. Video Muted