# Captur — Case Studies (full text) > This file contains the complete text of every Captur case study, optimised for LLM consumption. For a shorter overview see /llms.txt --- ## GoBolt Launches Next-Gen AI Proof of Delivery Technology with Captur URL: https://www.captur.ai/case-studies/gobolt-delivery Company: GoBolt | Industry: Delivery | Location: US & Canada | Published: 2025-03-29 GoBolt and Captur have joined forces to introduce meaningful innovation to the logistics sector. GoBolt is a tech-enabled logistics provider across the U.S. and Canada; Captur's on-device AI validates proof-of-delivery images in real time. ### Key metrics - **30%** — Reducing DNR in just one week - **96%** — User engagement with real-time AI - **4 weeks** — From integration to fully operational GoBolt and Captur have joined forces to introduce meaningful innovation to the logistics sector. GoBolt is a tech-enabled logistics provider serving mid-market and enterprise businesses across the U.S. and Canada. With a mission to simplify logistics, GoBolt built their own Warehouse and Transportation Management Systems to solve third-party logistics inefficiencies and deliver sustainable, integrated solutions. Captur is the leading on-device AI platform for growth stage companies providing logistics and transportation services. Captur's software validates images in real-time on any mobile device to help companies protect quality and grow their brand reputation as they scale. The company operates across the US, Europe, and Asia with global partners. ### The industry context: a sector ripe for innovation The last-mile of automation: While the logistics industry has made significant strides in areas like route optimization and real-time tracking, advancements in last-mile delivery and proof of delivery (PoD) systems have been harder to realise. Many providers are now exploring modern technologies to enhance visibility, reduce disputes, and improve the customer experience. The DNR dilemma: Delivery Not Received (DNR) claims are a persistent pain point within the industry, costing time, money, and customer trust. Many retailers still rely on outdated processes and manual reviews, leading to inefficiencies and limited accountability. "We saw Delivery—not just the act of it, but the proof of it—as one of the last unresolved friction points in the customer journey. DNRs are a tough problem for retailers and couriers alike, and we knew AI could offer a smarter, more scalable solution. Partnering with a forward-thinking team like GoBolt, who were already embracing technology at their core, made this an ideal collaboration to bring that vision to life." — Charlotte Bax, CEO & Founder at Captur ### The technology: what Captur and GoBolt have built What it does: Captur's AI-based PoD solution automates the detection of key delivery moments—like when a package is clearly visible at the doorstep—turning courier-captured images into actionable insights. How it's different: Unlike traditional PoD methods that require manual tagging or post-hoc dispute resolution, Captur's technology works in real-time, on-device, to verify delivery conditions. It is completely automated and integrates directly into existing driver apps. GoBolt's implementation: GoBolt became one of the first logistics providers in North America to fully integrate Captur's AI-powered SDK across its delivery operations. The rollout was seamless and GoBolt was fully operational in just four weeks. Integrated touchpoints: GoBolt replaced their existing PoD flow in the driver app with Captur's ReactNative SDK to achieve a live-scanning experience with AI feedback. ### The results: impact in weeks, not months Fewer DNRs: GoBolt saw a 30% drop in DNR claims reported in the first week, improving brand and shopper sentiment, while reducing internal support and dispatch costs. Better PoDs: Deliveries without a visible package in the image decreased by 20%, giving GoBolt and their customers more confidence in their delivery performance. Increased compliance: Approximately 96% of drivers re-attempted photo capture when shown a warning that not all PoD criteria were met—demonstrating strong engagement and trust in the AI's feedback. No added friction: Crucially, there was no increase in session time for drivers (< 2 mins), preserving speed and efficiency at the point of delivery. ### What this means for the logistics industry Smarter oversight for retailers: Retailers partnering with providers like GoBolt can now access indisputable, AI-verified PODs—helping them improve their shopper and delivery experience. Proactive monitoring: With real-time insights, operations teams can identify potential PoD issues as they happen, not after the fact. Fewer lost packages, happier customers: Improved visibility means happier customers, fewer disputes, and fewer refunds across the board. ### Final thoughts With AI-powered Proof of Delivery now fully deployed across GoBolt's operations, the next evolution on the horizon is Proof of Address—a technology designed to ensure every package reaches the correct doorstep, with precision and confidence. GoBolt's collaboration with Captur demonstrates that AI in logistics isn't just a buzzword—it's a practical, scalable solution to one of the industry's most stubborn problems. As more carriers adopt intelligent PoD technology, we can expect a new standard for last-mile delivery: one that's faster, clearer, and fairer for everyone involved. ### Testimonial > "The ROI was immediate and measurable. We integrated Captur's SDK in four weeks and saw DNR claims drop 30% in week one. What impressed me most wasn't just the AI accuracy, it was that delivery associates didn't slow down. Any tech that adds friction at delivery kills operational efficiency. Captur proved you can have both higher quality and faster throughput, which frankly, most 'AI solutions' in logistics can't deliver on." > — Heindrik Bernabe, CTO & Co-Founder at GoBolt --- ## AI-Guided Parking: The Key to Safer Free-Floating Cities URL: https://www.captur.ai/case-studies/micromobility-atom-mobility Company: Atom Mobility & Hoog | Industry: Micromobility | Location: Estonia | Published: 2024-07-30 Atom and Captur are helping smaller cities across Europe launch micromobility rental schemes without having to pay for expensive infrastructure changes (mandatory parking zones), adopting a free-floating setup. With Atom's suite of micromobility technology and Captur's AI-guided parking solutions, operators like Hoog are able to scale with ease while reducing 80-90% of their time reviewing parking images. ### Key metrics - **82%** — Bad Parking Incidents Eliminated - **80-90%** — Reduction in time spent reviewing parking photos - **7** — New regions entered in the last 12 months ### Free-floating without the chaos Smaller European cities want the benefits of micromobility but often can't afford the infrastructure investment required for mandatory parking zones. Free-floating schemes — where riders can park anywhere within a service area — are far cheaper to deploy, but they come with a major downside: bad parking. Without a way to verify where and how vehicles are parked, operators like Hoog faced growing complaints from city councils and residents. ### AI-guided parking at scale By integrating Captur's AI-guided parking solution through Atom Mobility's platform, Hoog was able to validate end-of-ride parking photos in real time. Captur's models detect over 30 parking scenarios — from blocked pavements to vehicles left in roadways — and provide instant feedback to riders before they end their trip. The result is a self-correcting system that eliminates the need for manual photo review by operations teams. ### Scaling with confidence With 82% of bad parking incidents eliminated and an 80–90% reduction in time spent reviewing parking photos, Hoog was able to expand into seven new regions in a single year. More importantly, the data generated by Captur gave Hoog a compelling story for city councils — demonstrating responsible operations and proactive parking management. What started as a compliance tool became a competitive advantage, helping Hoog win new city partnerships and build a culture of responsible parking from day one in every new market. ### Testimonial > "The integration of AI-driven parking analysis, has not only helped strengthen our relationships with existing city councils but has also made Hoog an attractive partner for future collaborations. Furthermore, Captur has played a pivotal role in our successful expansion into new cities this year, enabling us to proactively build a culture of responsible parking from day one in new markets." > — Holger Ollema, Co-Founder of Hoog Mobility --- ## On the Paris parking case URL: https://www.captur.ai/case-studies/micromobility2-paris Company: Captur | Industry: Micromobility | Location: Paris | Published: 2024-07-30 How do people really park in Paris? Captur uses AI and parking data to separate rider behaviour from infrastructure gaps — and to support safer, more sustainable micromobility in the 15-minute city. ### Key metrics - **78%** — of rides end with safe parking - **80%** — of bad parking tied to signage or lack of suitable parking spots - **30** — parking scenarios Captur can detect - **3 seconds** — typical time for parking feedback ### Moving cities into a sustainable future Micromobility is already paving the way for decarbonised cities, with clear environmental and social benefits. However, as new modes of transport gain popularity, more vehicles on the road lead to greater safety risks. At Captur, we want to dig into the data to see just how well, or poorly, people park. Benefits: • Environmental impact on urban air quality and decarbonisation • Reduction of traffic and reduced burden on public transport in cities and towns • Efficient and accessible transportation Challenges: • Cities must evolve infrastructure to accommodate new modes of transportation • Vehicles cluttering streets and causing potential hazards for road users • Requires behaviour change of shifting away from cars and taxis in city centres ### Keeping Paris the 15 minute city The future of micromobility in Paris has been debated over the last few months, with concerns around e-scooters and e-bikes cluttering the streets. Captur wants to ensure the safe adoption of micromobility by utilising AI to give riders feedback on their parking in real time and to monitor potential high-risk areas in the city. ### Parking in Paris Distribution of rider parking across the city. ### Parisians park better According to our data, Parisians tend to park better (according to local restrictions) than many other European cities including Copenhagen, Rome and Madrid. ### API + SDK user guidance Over a four-month period, we identified areas of unsafe parking in Paris and what might be the cause of bad parking — riders or infrastructure? ### Paris parking heat map Our data is gathered from micromobility companies operating in Paris between October 2022 and February 2023. ### Trends Bad parking: The most frequent reasons for bad parking are when Parisians… • Park next to cars or other vehicles • Park in the road • Park outside of designated bays Good parking: Parisians are relatively good at: • Parking in the bay (when clearly marked) • Or in bike racks • Attempting to park in busy bays Insufficient information: Some photos are just not good enough: • Photos taken too close up to the scooter • Blurry or dark photos • No scooter visible in the photo ### Recommendations 1. Install clear signage next to parking bays 2. Provide guidance to riders before they finish parking 3. Expand capacity and number of parking bays in high-risk areas ### AI detection Our models work across multiple parking regulations, including free floating and mandatory parking zones, and provide feedback on parking within three seconds. Cities use different operating models — from purely free-floating schemes to mandatory parking bays or a mix of both. Captur trains and deploys models so the same on-device pipeline can enforce the rules that apply in each market. ### How we classify parking Each end-of-ride image is evaluated against local rules and returned as one of four outcomes: Good parking — the vehicle is safely parked and out of the way. Bad parking — the vehicle is parked unsafely and needs to be moved. Improvable parking — the vehicle is not a danger to anyone, but the rider could have parked more considerately. Insufficient information — there was not enough information in the image to rate the parking condition. ### Parking scenarios Here are just a few examples of the parking situations our models can recognise in the wild — from compliant bays and racks to hazards on the pavement or in the road, and common photo-quality issues that require a retake. ### Conclusion Captur • Provide real-time parking guidance to riders. • Share insights and analysis to help inform where new parking zones or infrastructure is needed. • Help operators run and expand their fleets safely. Operators • Promote safer parking among riders using real-time prompts as well as post-trip incentives. • Work closely with arrondissements and parking officials to identify problem areas. • Collaborate with other operators to avoid overcrowding. City of Paris • Install clear signage next to parking bays. • Expand the capacity and number of parking bays in high-risk areas. • Highlight arrondissements and operators setting the example for safe parking standards. --- ## Zapp scales a global fleet with Captur URL: https://www.captur.ai/case-studies/delivery Company: Zapp | Industry: Delivery | Location: London, United Kingdom | Published: 2025-06-12 When time is money, creating a scalable process is key for rapidly-growing industries like last mile. For already busy fleet managers, creating an easy, automated process, is a priority for quickly scaling businesses ### Key metrics - **5 hours** — saved per week - **20.3%** — increase fleet uptime - **10 days** — faster to fix damage report issues ### The challenge Last-mile delivery is one of the fastest-growing sectors in logistics, and Zapp needed to scale its fleet operations quickly across multiple cities. Fleet managers were drowning in spreadsheets, manually tracking vehicle condition, damage reports, and compliance checks. With hundreds of riders joining each month, the existing process simply couldn't keep up — and missed damage was costing thousands in unrecovered repairs. ### The solution Captur's on-device photo validation was integrated into Zapp's rider onboarding and daily check-in flows. Riders now capture standardised photos of their vehicles at the start and end of every shift. Captur's AI validates each image in real time — checking angles, lighting, and completeness — so fleet managers no longer need to chase riders for missing or unusable photos. ### From spreadsheets to a single platform Before Captur, damage reports were scattered across emails, WhatsApp messages, and shared documents. Information was regularly lost, and disputes over pre-existing damage were difficult to resolve. With Captur, every inspection is timestamped, geo-tagged, and stored in a single platform accessible to stores, suppliers, and fleet managers. The result is a clear audit trail that has dramatically reduced the time it takes to resolve damage claims — from weeks to days. ### Results Within the first three months of deployment, Zapp saw a 20.3% increase in fleet uptime and saved over five hours per week in manual administration. Damage report resolution times dropped by ten days on average, and the operations team gained real-time visibility into fleet condition across all locations. ### Testimonial > "Captur transformed our fleet process from dependence on spreadsheets to a one platform reporting system. It enables the stores and suppliers to benefit from real-time data and provide effective resolve for a great uptime" > — Nadeem, Fleet Manager --- ## How AI is riding to the rescue to keep streets safe in a changing world URL: https://www.captur.ai/case-studies/micromobility-3-unitary Company: Unitary | Industry: Micromobility | Location: London, United Kingdom | Published: 2024-07-30 Captur and Unitary are joining forces to make micromobility work for everyone by giving suppliers, customers and local authorities the AI tools they need to keep streets safe and uncluttered. ### The problem on our streets Micromobility has transformed urban transport across Europe, but it has also created real tensions with pedestrians, local authorities, and accessibility advocates. Poorly parked e-scooters block pavements, obstruct wheelchair ramps, and create hazards for visually impaired pedestrians. Several charities have called for rental schemes to be scrapped entirely — putting the future of shared micromobility at risk. ### A new approach to street safety Captur and Unitary are combining their AI capabilities to give operators, councils, and cities the tools they need to enforce responsible parking at scale. Captur's on-device vision validates parking photos in real time, while Unitary's content moderation AI flags unsafe or obstructive placements. Together, the partnership provides a feedback loop that nudges riders toward better behaviour without requiring expensive physical infrastructure. ### Making micromobility work for everyone The joint solution is designed to address the concerns of all stakeholders. Operators get automated compliance data for regulators. Councils get visibility into parking patterns and hotspots. And pedestrians — particularly those with disabilities — benefit from fewer obstructions on pavements. By making parking accountability a built-in feature rather than an afterthought, Captur and Unitary are helping to secure the long-term viability of shared micromobility in cities worldwide. ### Testimonial > "Visually impaired and blind people have been particularly vocal about their concerns, with several charities calling for micromobility schemes to be scrapped" > — The Guardian, 2022 --- ## Buzzbike tracks damage and builds trust with Captur URL: https://www.captur.ai/case-studies/micromobility-4-buzzbike Company: Buzzbike | Industry: Micromobility | Location: London, United Kingdom | Published: 2024-07-30 Buzzbike's collaboration with Captur led to efficient tracking of bike conditions and a fourfold increase in settled damage claims, boosting customer trust and satisfaction. ### Key metrics - **4x** — increase in damage claims settled - **4.8** — Trustpilot rating ### A trust problem Buzzbike operates a subscription bike service in London, providing commuters with high-quality bikes at a flat monthly rate. But when bikes were returned with damage, proving who was responsible — and when the damage occurred — was nearly impossible. The result was a backlog of unresolved claims, frustrated customers, and significant financial losses on unreported damage. ### Photo-verified accountability With Captur integrated into Buzzbike's check-out and return process, every rider now captures AI-validated photos of their bike at both ends of the rental. The system ensures images meet quality standards and captures the right angles, giving the operations team a clear before-and-after record for every trip. No more blurry photos, no more missing evidence. ### Rebuilding trust with riders The transparency created by Captur's visual audit trail changed the dynamic between Buzzbike and its riders. Customers appreciated knowing they wouldn't be blamed for pre-existing damage, while Buzzbike could confidently settle legitimate claims. The result was a fourfold increase in successfully settled damage claims and a Trustpilot rating of 4.8 — proof that accountability builds, rather than erodes, customer trust. ### Testimonial > "The whole team is seeing the same information, and there's massive comfort in knowing that information isn't being lost." > — Charlotte, Head of Rider Happiness