bitdrift AI
Gives an AI agent full, unsampled access to what's actually happening on a billion-plus mobile devices' worth of app sessions, so it can triage and fix a crash or bug itself instead of an engineer waiting days for the next app release to get more data.
🔗 Visit bitdrift AI
Description
Mobile observability has traditionally meant sampled data — you get a fraction of sessions, enough for a human to spot trends but not enough for fine-grained, on-demand investigation, and adding new instrumentation means shipping a new app release and waiting for adoption. bitdrift AI, built by the team that engineered Lyft's mobile observability, removes that sampling: it gives full-resolution access to live sessions, targeted cohorts, and on-demand telemetry.
The real differentiator is that this data is exposed specifically for AI agents to consume — via CLI, a public API, and purpose-built Skills — so an agent can query millions of devices in real time, create new instrumentation on the fly without a release cycle, and iterate through a bug investigation in a tight feedback loop rather than escalating to a human with limited data. Early users report a 10x improvement in mean-time-to-resolution as a result.
💬 Our review
The short version: if your mobile engineering team is bottlenecked by sampled crash data and slow release cycles for new instrumentation, bitdrift AI's unsampled, agent-queryable data is aimed squarely at collapsing that bottleneck — though as a newly launched product, pricing isn't public yet.
Compared to established mobile observability players like Firebase Crashlytics, Datadog, or New Relic — all of which are built primarily for human dashboards and sampled data — bitdrift AI's bet is that the next wave of mobile debugging will be agent-driven, and it's architected data access around that from the start rather than bolting AI features onto an existing sampled pipeline. That's a forward-looking wager: teams not yet using AI agents for on-call/triage work won't get the full value, and $15M in seed funding plus a fresh launch means the product is still proving itself against incumbents with years of enterprise trust.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Tarification non publiée, probablement freemium/enterprise
Pros
Données mobiles non échantillonnées, en temps réel
Accès conçu spécifiquement pour des agents IA (CLI, API, Skills)
Instrumentation à la volée sans nouveau cycle de release
10x d'amélioration du MTTR rapporté par les premiers utilisateurs
Cons
Tarification non publique
Produit tout juste lancé, moins de recul que les acteurs établis
Valeur maximale seulement si l'équipe utilise déjà des agents IA pour le triage