Blog

Mobile AI is about trust. Captur and Datadog discuss observability for on-device models — clear visibility into behaviour and faster, more reliable improvements.

A curated map of 29 companies building AI outside the cloud — from edge silicon and on-device LLMs to cross-platform SDKs and embodied applications. Device-edge scope, not CDN edge.

Shrinking model size on mobile, without sacrificing performance.

We've achieved SOC 2 Type 2 with Insight Assurance and Complyance—a sustained audit of how our controls operate over time, not a one-day snapshot. Here's why it matters for AI companies and what it means for our customers.

The manifesto behind the launch of Bleep AI.

Written by Justin Powell, Senior Edge Computing Engineer at Captur.

Captur and Veo are bringing AI parking guidance to 50+ U.S. markets—real-time compliance checks in-app so riders fix issues before they walk away, and cities get clearer streets.

Captur improves visibility between cities and micromobility operators by offering real-time feedback on parking compliance. Shared dashboards and objective imagery reduce back-and-forth about what actually happened on the street, so conversations move from debate to decisions.

In today's rapidly evolving supply chain landscape, businesses face numerous quality challenges. Here we focus on three that show up again and again in audits and ops reviews—and what leading teams are doing differently to catch issues earlier without slowing throughput.

Charlotte Bax and Philip Botros walk through a practical AI roadmap template, key metrics, and how to scope AI projects for impact.

In the realm of data security, the integration of image processing technologies presents both opportunities and challenges. Security leaders often ask the same practical questions before they sign off on a deployment; this post collects the ones we hear most and how we answer them with architecture, not slogans.

Ever wondered what Captur does? We're a visual AI company, but that label can mean a lot of different things. This post walks through how modern image recognition actually works in production—from the camera pipeline to the model—and where on-device validation changes the economics of a rollout.

The way consumers shop has changed dramatically over the years. Expectations for speed, proof, and accountability now show up in logistics and field operations—not only in retail—and that shift is why photo evidence is treated as a product surface, not an afterthought.

According to Gartner, supply chain firms are expected to witness a two-fold increase in machine automation. We unpack four ways AI is already changing last-mile delivery—where the ROI is clearest, what breaks if you skip edge validation, and how to roll out without surprising drivers or customers.

Charlotte Bax and Nathan Sansby on AI in logistics — full written recap: warehouse automation, routing, sustainability, customer experience, Captur and Resolvable case studies, and agentic versus assistive AI.

By integrating AI technologies into last-mile delivery operations, companies can not only improve efficiency and reduce costs but also contribute to a more sustainable and environmentally friendly delivery ecosystem.

According to McKinsey and Company, AI has the potential to add $13 trillion to the global economy, but is your organization equipped to capture that value? This guide frames the adoption gaps we see most often in enterprises and a practical sequence for closing them without boiling the ocean.

This certification reinforces our commitment to maintaining the highest standards of security, availability, and confidentiality. SOC 2 Type 1 is an important milestone on the path to sustained assurance—it documents how controls are designed today as we continue to mature the program.

In this blog post, we discuss the two most common AI metrics: precision and recall. If you are new to model evaluation, understanding the trade-off between them is the fastest way to read vendor claims critically and to set thresholds that match your real-world cost of errors.

How major delivery and retail companies described AI in Q2 2024 earnings — and what it means for logistics strategy.

A 10-step guide to stages, expertise, time, and ROI — decide whether to build or buy your visual AI solution.

Mechanisms behind machine vision, accuracy and latency in the user journey, production constraints, and where image recognition helps or hurts.

Lightweight web prototypes, faster validation with Gemini, and real product value from listing.captur.ai — how we shorten the path from idea to impact.

Bolt, Lovable, Replit, and Cursor — what we looked for when prototyping with commercial teammates, and how each tool stacks up for sharing, handoff, and ease of use.