4 min read
Source: Cojali — September 8, 2026
Spanish diagnostics specialist Cojali has unveiled Jaltest AI: Next Wave Workshops, the first diagnostic ecosystem for commercial vehicles that combines applied artificial intelligence, multilingual voice recognition, and augmented reality in a single workflow. Announced at Automechanika Frankfurt 2026 and shown live in Hall 3, Stand E80, the platform targets a problem every truck and bus workshop knows firsthand: the technician who has to stop working to walk over to a screen and look something up.
What Jaltest AI Actually Covers
Jaltest AI is not a new scan tool in the traditional sense. It is a software-and-hardware layer that sits on top of Cojali's existing Jaltest diagnostics platform for commercial vehicles and changes how the technician interacts with it. The core idea is hands-free, eyes-on-the-job operation.
Until now, Cojali argues, the workshop workflow forced the technician to adapt to the tool: walk over to the screen, dig through technical documentation, then switch back and forth between the vehicle and the computer. Jaltest AI turns that dynamic around by presenting the right information at the moment it is actually needed, so the work never has to stop. In practice, the mechanic can request fault-code analysis, guided diagnostics, component locations, step-by-step procedures, or remote expert support entirely by voice, with both hands free.
Three technologies do the work together. An applied AI layer analyzes live vehicle data, technical documentation, and Cojali's accumulated technical-support knowledge in real time, then serves context-specific guidance tailored to the job in progress. Multilingual voice recognition lets the technician talk to the system in natural language, requesting fault-code analysis, guided diagnostics, component locations, step-by-step procedures, or remote assistance from an expert without touching a keyboard. Augmented-reality glasses then project that information — wiring diagrams, diagnostic readings, and repair instructions — directly into the technician's field of vision, overlaid on the vehicle in front of them.
According to Cojali, the combination delivers measurable results on the shop floor: shorter diagnosis and repair times, a lower margin of error, a greater ability to tackle complex repairs, and immediate access to specialist knowledge regardless of a technician's prior experience. That last point is the quiet headline — the system flattens the learning curve instead of just speeding up an expert. "The technician has the full intelligence of the system at their disposal exactly where and when they need it," said Venancio Alberca, Cojali's president and CEO.
Why It Matters for Heavy-Duty and Fleet Technicians
Commercial vehicle repair has always been information-intensive. A modern truck carries dozens of ECUs across engine, transmission, braking, and telematics systems, and the wiring documentation for a single chassis can run to thousands of pages. Traditional workflows force a technician to leave the vehicle, consult a laptop, and return — repeatedly. That back-and-forth is where minutes quietly turn into hours.
Hands-free diagnostics change the economics of that workflow. A technician who can ask a question aloud and see the answer projected onto the vehicle keeps both hands on the job and stays in position under the hood or in the cab. For a shop that already runs a heavy-duty diagnostic tool, an AI layer that overlays guidance on top of it is an efficiency upgrade rather than a replacement. The appeal is sharpest for fleets, where downtime is priced in revenue per hour and a single misdiagnosis can cascade into a repeat visit.
The barrier-lowering effect matters for independent shops as well. Commercial vehicle work has historically been hard to break into because it demands deep, make-specific knowledge. Tools that flatten that learning curve lower the cost of entry. A general shop that moves up from a passenger-car diagnostic setup to a full diagnostic computer can begin taking on truck work without hiring a dedicated heavy-duty specialist on day one.
There is a retention angle too. The skilled-technician shortage is a real constraint on shop growth, and guidance tools that bring a junior mechanic up to speed faster are increasingly being weighed as a recruiting and training asset, not just a repair aid. A platform that effectively puts a senior expert's knowledge in front of every bay is a way to scale experience without waiting years to build it.
What's Next for AI-Assisted Truck Diagnostics
Jaltest AI points to where the broader aftermarket is heading: the tool stops being something the technician goes to, and becomes something that comes to the technician. The same pattern — AI guidance, voice control, and head-up information — is already appearing on the passenger-car side, and Cojali's announcement suggests the commercial-vehicle segment is now catching up.
None of this removes the need for solid underlying hardware and current software. An AI assistant is only as good as the data it can reach, which is why keeping a diagnostic software subscription current remains the single most reliable way to protect a tool investment. For shops watching the commercial-vehicle space, the takeaway is straightforward: expect AI-assisted, hands-free diagnostics to move from trade-fair novelty to shop-floor standard faster than the last generation of scan tools did.
Written by James Mitchell, Senior Technical Editor at vxdas.com
