Economic & Operational Intelligence for Equipment Owners
Canary connects your contracts, invoices, equipment records, and maintenance history into a single platform, so you stop overpaying and capture the full value of every agreement you have already signed.
Hidden and Significant Cost
Coverage is bought, renewed, and managed in the dark.
Most operators cannot tell you exactly what every agreement covers, when it expires, or what entitlements remain unclaimed. SLA violations go untracked. Renewals happen on autopilot. Services and benefits, which have already been paid for, are regularly missed.
Our Solutions
Canary is built around the full equipment lifecycle: choosing the right coverage, staying compliant with it, and recovering everything it owes you.
Walk into every renewal knowing what the agreement actually delivered.
Renewals happen on autopilot because nobody has the record to push back with. Canary keeps score over the life of each agreement, so you negotiate from evidence instead of memory.
Learn more →Get billed what you agreed, not what the rate card says.
Service invoices are approved by people who never saw the contract. Canary checks every line against the governing agreement and tells you what to pay, what to dispute, and what needs a closer look.
Learn more →Never miss an obligation your agreements hold you to.
A missed service interval or unauthorized repair can void your own coverage, costing more than the repair itself. Canary tracks every obligation and flags gaps before it becomes a problem.
Learn more →A maintenance plan built from your contracts and industry best practices.
Most maintenance is still reactive, based on guesswork, and manually tracked. Canary is a maintenance operating system that tells you exactly what you need to do and when, in the most cost-effective way.
Learn more →Get what you are owed, without the headache along the way.
When equipment fails or a contractor misses a commitment, Canary generates and files the claim. Entitlements like free inspections or replaced parts are automatically scheduled.
Learn more →Our Mission
A neighborhood bakery's industrial cooler broke one summer. They called the nearest repair shop, got it fixed, and moved on. What they didn't know was that the repair voided their warranty. When the same fault returned six months later, the coverage they'd been paying for all along was gone, and the replacement came out of their own pocket.
That story isn't unusual. Most operators aren't losing money because they lack coverage. They're losing it because the agreements governing their equipment are long, dense, and written by parties who lose nothing when a claim goes unmade. Contracts get signed and filed. Entitlements lapse. Obligations go unmet. By the time equipment fails, nobody remembers what the document actually said.
Canary was built to close that gap. We take the documents that govern your equipment coverage and turn them into something you can act on: what you're covered for, what you've already paid for but haven't claimed, and what you need to do to keep that coverage intact. No legal training required, and no extra work for teams already running lean.
The Team
Canary is built by people who have worked in industrial operations, enterprise AI, and mission-critical software. We know what it takes to get adoption on the plant floor.
Co-Founder
Tennyson has +5 years experience equipping traditional industry with the digital tools required to be competitive in today’s environment of rising costs. He most recently worked as a Director of AI Solutions for a startup aimed at improving product quality for the world’s leading manufacturers, and was previously a technology-focused consultant at Boston Consulting Group (BCG). Tennyson is from Colorado, studied economics at the University of St Andrews, and is a Schwarzman Scholar.
LinkedIn →Co-Founder
Ryan has over 5 years of experience working with AI models, machine learning, and system optimization. He previously served as a Vice President of Applied AI and Machine Learning at J.P. Morgan Chase, where he built machine learning systems for large-scale financial data and learnt how to orchestrate AI workflows at scale. He brings deep expertise in data engineering and AI applied to industrial systems. Ryan is from Johannesburg, South Africa, and studied at the University of St Andrews and MIT.
LinkedIn →We're building the team. Talk to us →
Get in Touch
Whether you're running a pilot, evaluating options, or just curious, we want to hear about the downtime and warranty problems you're dealing with.