Not a chatbot. A team of AI coworkers that work inside your ERP, your inbox and your spreadsheets, finish the job, and hand back the file — under rules you set, with a record you can show anyone.
A simulated morning, using the platform's real tools. Every line is something Clovar agents do today.
An AI coworker is only useful if it can reach your real data. Clovar agents read and act inside the systems your business already depends on — no migration, no rip and replace.
Agents query part data, pricing, stock and purchase history straight from your ERP through the Model Context Protocol. They answer with your numbers, not guesses.
Gmail and Microsoft 365 with real-time push. Agents triage, draft, attach and send — and anything going out can wait for your approval first.
Paste in an OpenAPI spec and Clovar builds the connector. Every connector runs isolated, code-signed, with its permissions reviewed — new integrations don't mean new blind spots.
Every role ships with the job description, the tools, the operating rules and the escalation path already wired. Pick one to see how its day goes.
Also in the box: Support Escalation, Executive Briefing, Security Analyst, and five ingester roles that live on supplier feeds — price updates, datasheets, end-of-life notices, last-time-buy warnings and lifecycle bulletins. Or write your own: a role is just a persona, a toolset and a contract.
Most AI tools give you text in a chat window and leave the job to you. Clovar agents finish it — and hand back the spreadsheet, the document or the report you were going to build.
| Part | Rev | Qty | Unit cost | Lead time | Last sale | |
|---|---|---|---|---|---|---|
| 46 | PN-20481 | C | 120 | $14.20 | 12 d | 2026-07-30 |
| 47 | PN-20482 | A | 40 | $3.85 | 5 d | 2026-08-11 |
| 48 | PN-20490 | B | 600 | $0.92 | 21 d | 2026-08-14 |
| 49 | PN-20511 | — | 15 | $212.00 | 35 d | 2026-05-02 |
| 50 | PN-20517 | D | 250 | $7.40 | 9 d | 2026-08-20 |
| 51 | PN-20530 | A | 80 | $28.15 | 14 d | 2026-08-26 |
Clovar agents are not prompts in a loop. They remember, they own work across days, they hand off to each other, and they get better at the job.
Agents run on a schedule, react to an event, or answer when spoken to. Work happens overnight without anyone prompting it.
Managers and direct reports. They delegate down, escalate up, brief their peers, and borrow a specialist from another department when a job needs one. Put several in one room with you and steer.
Facts and relationships persist in a knowledge graph; the relevant history is found by meaning, not keyword. Tuesday's agent knows what Monday's learned.
Tasks carry dependencies, priorities and locks so two agents never fight over one job. Cases stay open across days, wake when a reply lands, and close when they're actually resolved.
For bigger jobs an agent lays out what it intends to do before it does any of it. Read it, change it, approve it — then watch it execute exactly that. When it's stuck, it asks.
Lessons from their own work are promoted into how they operate; A/B test two variants and keep the winner. Spend is tracked per agent against live rates, with a ceiling that stops work rather than surprising you.
Every turn follows the same seven steps — which is why it can be governed at every one of them.
A schedule fires, an email lands, a workflow reaches its turn, a colleague delegates — or someone simply asks.
Memory, knowledge, open tasks and unread briefings come together into one picture, so the agent starts informed.
The model works through the job in the agent's role and persona — planning the steps, not answering a single question.
Every tool call is checked against what that agent is allowed to touch before it runs. Records, files and external systems update for real.
Anything with a consequence is weighed by risk, cost and how much trust this agent has earned. It proceeds, waits for approval, or is refused.
High-stakes actions queue with the evidence and the reasoning attached. Approve, reject, edit the draft, or ask for more.
Facts land in the knowledge graph. The conversation is summarised with the entities that mattered — so the next agent starts ahead.
Most teams won't let AI near anything that matters because they can't predict or prove what it did. Clovar is built the other way round: agents earn scope, every consequential action is weighed against your rules, and all of it is on the record.
Each agent works under a versioned contract: its role, the systems it may touch, what it must never do, the evidence it has to produce, and what it may spend. Contracts move through draft, staging, certified and production, and become immutable once published — changing the rules means a new version and a new sign-off.
Agents graduate by proving themselves, one level at a time.
Every approved or rejected action carries a structured account: what triggered it, how the agent reasoned, which policy applied, what else it considered, and what actually happened. When someone asks why an agent did something six weeks ago, you have the answer rather than a log line.
Run an agent in simulation to see what it would have done. Certification suites test a contract before production, and past runs replay as regression tests.
Every action that touches the outside world is written to a ledger before it happens. Secrets are referenced by name, never seen. One stop control halts everything an agent has in flight.
Resolution rate, approval rate, value delivered and a health score — so whether this is paying off has a number attached.
We host it, run it, secure it and keep it current. You bring the work. Clovar Cloud is onboarding a limited number of businesses — tell us about yours.
The complete platform as a service — nothing to install, nothing to operate, and a team that already knows how to get agents doing real work.