Reliability intelligence for EV charging networks
Chargers that say available but deliver nothing. Sessions that never start. Energy quietly leaking out of your network. Tadit finds these faults, files the issue where your team works, and explains the why when you ask. All on top of the CPMS you already run.
SaaS or private deployment · every credential encrypted with keys unique to your workspace
Flagged it on Tuesday and filed the ticket. One question to the agent found the frozen meter, before the weekend traffic arrived.
A driver pulls up, plugs in, gets nothing, and leaves. Your dashboard stays green. No alarm. No ticket. Just lost revenue, and a driver who won't come back. When someone finally notices, an engineer loses half a day in the logs. Most of these faults are never investigated at all.
You can't fix what you can't see.
It's not another charging platform. It watches the one you already have, and does three things, continuously, for every charger you operate.
Thirteen fault types caught out of the box, plus the ones no rule can catch: every charger learns its own normal, so drift, a firmware version failing as a group, or sessions ending the wrong way get flagged early. Faults are ranked by how busy the charger is, so you fix what drivers feel first.
Every fault: 45-day history · event log attached
Ask the AI agent about any flagged charger, and it investigates the way your best engineer would: reads its history, checks the manuals, rules things out, and shows its work. Half a day of log-digging becomes a five-minute read.
The meter stopped recording after last week's firmware update. Sessions run, but no energy is counted. The vendor's bulletin recommends rolling back to the previous version.
Every fault arrives as one well-briefed ticket in Jira, ServiceNow or Slack, or a webhook to any system you run, with its history and severity attached. Not a hundred raw alerts for your team to wade through.
Charger 04 delivers no energy · 9 sessions, 0.0 kWh
Severity high · worsening · 4th recurrence
Attached 14-day history and event timeline
Point the agent at any charger, a fresh flag or a question of your own, and it investigates like your best engineer on their best day: reads the charger's history, weighs the likely causes, checks your manuals and service bulletins, and lands on a verdict in minutes. You decide when it runs.
18 steps · every one logged and reviewable
Tadit is an MCP server. Connect the AI assistant your team already runs, Claude, ChatGPT or Gemini, and ask straight away. It answers from live fleet data, read-only and scoped to your workspace. No dashboard to learn, no query to write.
via MCP · OAuth 2.1 · read-only · scoped to your workspace
Decide once what should happen for each kind of fault. Tadit does it every time after that: instantly, at 2 a.m., without anyone on call.
Deduped · one ticket per fault, history attached
Tadit measures the energy each fault leaks, per station and per cause, so you fix the most expensive problems first and walk into your ops review with numbers, not anecdotes.
Works with any CPMS · vendor-neutral
Tadit connects to your charging platform, or straight to your chargers. No new hardware, nothing replaced. First alerts the same day, while behavioural baselines build in the background. New platforms are added on request, and your reliability data stays vendor-neutral, so you can compare hardware on facts.
Use the hosted SaaS and be live in days, or run Tadit as a private deployment inside your own infrastructure when your data can't leave home. Same product, same detection, either way.
Every credential your workspace holds, CPMS tokens, AI keys, integration secrets, is encrypted with keys unique to your workspace. No shared secrets, no cross-workspace access.
For your IT team: OCPP 1.6 & 2.0.1 · MCP server (OAuth 2.1, read-only) · Enterprise SSO · SaaS or private deployment · Encrypted at rest, keys unique to your workspace · Your own AI keys (OpenAI or Gemini)
Tadit spots the fault, files the issue, and explains the why when you ask. Every confirmed verdict makes it sharper. That's the loop.
30 minutes. We bring the product, you bring the questions.