ZynoviqYour agent doesn't just answer. It acts. Test the actions.
An agent can explain a rule perfectly and still post the wrong entry, call the wrong tool or approve what it should have escalated. Zynoviq gives agent companies held-out professional scenarios with the expected action, not just the expected answer, so you can see what your agent does when the work is real.
What goes wrong without it
- Answer-level tests miss agent failures. The agent reads the right document and picks the wrong field, or chooses a search tool when it should have looked up the rate table.
- It follows the happy path. The invoice has an exception every practitioner would spot; the agent processes it anyway.
- It acts when it should have stopped. It posts before a required check, or changes a record it should only have flagged.
- Releases change behaviour silently. A new model, prompt, tool or retrieval source alters which cases pass, and nobody re-runs the old ones.
- Enterprise buyers ask for evidence before they let an agent act on their books, and a demo is not evidence.
What a scenario looks like
- 01Synthetic scenarioA supplier invoice with a reverse-charge supply and a missing field.
- 02Expected reasoningWhich rule applies, and why.
- 03Expected tool useWhich lookup or source the agent should consult.
- 04Expected actionHold the posting and escalate with a reason.
- 05Failure criteriaWhat a professional would count as wrong.
Illustrative The example is illustrative. Real scenarios are agreed in your mission specification. How it works.
What you get
What we mark
| Dimension | The question |
|---|---|
| Decision | Did the agent reach the conclusion a professional would? |
| Workflow | Did it follow the correct process, in the correct order? |
| Tool use | Did it choose the right tool or source, with the right inputs? |
| Action | Did it take the correct action, or correctly decline to act? |
| Policy | Did it respect legal, professional and organisational limits? |
| Escalation | Did it hand over to a person when the case required it? |
Structured fields are marked by fixed rules; free-text reasoning is marked by qualified professionals. Per case we capture the response, the tool calls and steps where the integration exposes them, the final outcome, latency and errors. Results come at overall, capability and case level, with severity and failure category. See a sample report.
From building to fixing
| Stage | What you need | What we supply |
|---|---|---|
| Building | Examples of correct decisions in your agent's input format | Reasoning records and worked cases in document form. What we make |
| Grounding | A reliable rulebook the agent can look up | Licensed packs of certified rules and worked examples, dated and cited. Catalogue |
| Tuning | Signals on what "better" looks like | Preference data on your agent's own answers. What we make |
| Testing | An honest exam before launch and each release | Diagnostic, then regression on every release. Continuous evaluation |
| Fixing | Material aimed at what failed | Improvement data from the test's failures. Improvement data |
One rule we keep for you: we never reuse your test cases as your training data. If the evaluation set leaks into training, the score stops meaning anything. Training and test separation.
How you start
- Test your AI
the free 25-case GST sample, run on your agent in your test environment. A short report within about two weeks shows where it goes wrong and why. Test your AI.
- AI Quality Diagnostic
about 100 cases on the workflow where a wrong action would cost most. Ends with the question: shall we run this every time you change your agent? The diagnostic.
- Regression and red team
the regression set runs on every release; a red-team engagement looks for the failures nobody has written down yet.
An illustrative example
Illustrative An agent company sells an invoice-processing agent that proposes GST treatment and posts documents in SAP. The diagnostic runs about 100 synthetic invoices in the company's sandbox. The agent handles plain credits well; on reverse-charge supplies from a firm of advocates it posts as a normal purchase instead of self-invoicing under the reverse charge, and on one malformed invoice it posts rather than holding. Both become regression cases. After the next release the regression run shows the reverse-charge cases recovered and no new critical failures.
This example is synthetic, not a customer result. Example missions.
Next: a synthetic company to test agents in
Planned. A realistic synthetic Indian company, with ledgers, vendors, invoices and payroll whose correct outcomes are already known and certified. Your agent is dropped into it and works as it would for a customer; every entry, payment and filing it makes is marked against the known-correct result. Built once and licensed to many, it runs the same way on any platform. We will build it when agent companies ask for it; if that is you, discuss a mission.
Where agent companies use Zynoviq
- Finance and tax agents on SAP. Live today for GST. GST and finance agents · Joule agents · BTP apps.
- Custom agents on any stack. Custom agents · Tally and Zoho.
- Agents sold to enterprises that ask for evidence before buying. Evidence · Software vendors and partners.
We never test products made by Zynoviq's Enterprise AI division, and our delivery teams are separate. How we stay separate.
SAP, Oracle, Microsoft, Salesforce, Tally and Zoho are trademarks of their respective owners. Zynoviq is not affiliated with or endorsed by them.
Agent companies — FAQ
Can you test an agent that takes actions in an ERP?+
Yes, in a sandbox or test environment you control. Our professionals define the expected action for each synthetic scenario (post, hold, reject, escalate) and we compare it with what the agent did, including the tool calls and steps where your integration exposes them. We never touch production. How tests run.
Do you work with agents built on SAP, Oracle or Salesforce?+
For GST and finance agents on SAP, yes; that is live today. GST testing for AI on Oracle is available; other Oracle and Salesforce process areas are on the roadmap and on request. SAP Joule agents · Oracle and Dynamics · Custom agents.
Is your red teaming a security test?+
No. Our red team uses professional adversarial scenarios: ambiguity, exceptions, contradictory instructions, policy manipulation, tool misuse and cases where the agent should refuse or escalate, plus agentic failure modes such as loops, wrong tool selection, premature actions and changing records it should not. It is not penetration testing or prompt-injection hacking. For security testing of your infrastructure, use a qualified security firm. Red team.
Where does the "correct action" come from for a configured workflow?+
Where law governs the decision, from the law. Where the decision follows your process, from your documented configuration and written policy, read with professional practice. We agree those sources in the mission specification before cases are written.