Better AI answers, with a record you can defend
Paresium Clara is our platform for exactly this. Clara sits between your AI and your business: it reads each customer message carefully, picks up what was really meant, and writes down every step. Your AI gets a clear summary. Your compliance team gets a complete paper trail.
What Clara looks at
For every customer message and every proposed AI action, Clara asks six questions before letting the answer go out.
What the customer really means
Beyond the literal words. Tone, urgency, and the things that were hinted at but not said.
Rules and policy
Your contract terms, internal rules, and the regulations your industry runs under.
Where they are in the workflow
What stage of the process this customer is at. What's already been said or done.
Who's allowed to do what
Is this person or system actually permitted to take this action, at this size?
Risk and exposure
What happens if this goes wrong. Including whether private customer information would be exposed or mishandled.
A complete record
Every step, every decision, every reason. Ready for your security or compliance team.
How Clara works
A simple flow that fits into any AI setup you already have.
Proposed agent action
High-stakes tool call
transfer_funds(amount: 50000, account: "external")
Clara verifies
Policy, risk, permissions, context
Outcome
Execute or halt with audit trail
Action blocked. audit_id logged for compliance review.
Four services. Buy any combination.
Clara is not all-or-nothing. It's four separate services that share one pipeline, and you pay only for the ones you use on each request. Start with one check, add the rest when you're ready.
Policy Check
Is this allowed?
Checks a message or proposed action against your business rules, contract terms, and the regulations that apply. Comes back with pass, warn, or block, and names the exact rule behind the call.
Buy it alone to screen every outbound AI message against your rules, even if another team runs the AI itself.
Risk Check
How badly could this go wrong?
Weighs the harm if this goes ahead: who could be affected, how severe it would be, and whether a person should look first. Flags the risks and the open questions.
Buy it alone as a second opinion on high-stakes requests before your own systems act on them.
Interpret Case
What is really being asked?
The full briefing: what the customer meant, the facts that matter, the recommended handling, and a clean prompt your AI can run with. This is the summary that makes answers better.
Buy it alone to make any AI you already run smarter about what customers actually want.
Governed Execution
Run the answer for me, safely.
We pick the right AI model for the job, run it with the briefing and your rules applied, keep your brand voice consistent, and record exactly what ran and what it cost.
Buy the full chain when you want one accountable pipeline from customer message to finished answer.
The two checks are also gates: if Policy Check or Risk Check says block, the later services never run and the credits held for them are released. Stopping early and charging honestly are the same mechanism.
An independent second opinion
Before any decision leaves Clara, it's reviewed by a judge that had no part in writing it. Easy cases get a fast, specialized reviewer. Hard cases go to a panel of AI models from different companies, each voting independently.
One dissenting vote is enough to block. Different models fail in different ways, so a panel that must agree is far harder to fool than any single AI checking its own work.
How the panel decides
- The judge reviews the finished briefing, never the drafting notes, so it can't just rubber-stamp.
- Panel members come from different AI companies, so their blind spots don't overlap.
- The most cautious vote wins. One block means blocked.
- Every vote and its reasoning is part of your record.
Where Clara fits
Clara isn't a chatbot or an AI model. It's the safety, understanding, and record layer that sits between your AI and the systems it talks to.
See the platform in action
Real examples, not marketing mockups. Below is what your AI receives from Clara for a real customer message: a briefing on what the customer actually meant, a suggested prompt your AI can use, and answering guidance to follow. Plus the full audit record.
A customer message in. A briefing, a prompt, and guidance back.
One API call. Your AI gets four things to work with: a verdict, the briefing on what the customer actually meant, a suggested prompt with the briefing baked in, and a short list of answering guidelines.
private_banking.support_inbox
"I tried to approve a wire to my CPA this morning and got blocked again. I have a closing tomorrow and need this fixed. This is the third issue this month."
approve_with_escalation_flag
Resolve a blocked outgoing wire and restore confidence.
Frustrated, time-pressured, pattern of complaints.
"Third issue this month" signals real churn risk.
Real-estate closing tomorrow is a hard deadline.
High-value, long-tenure client. Retention-sensitive.
You are an Acme Bank private-banking agent. The client is frustrated but the relationship is high value. Lead by acknowledging the closing tomorrow. Do not re-ask for wire details, they are already on file. Offer immediate human escalation in your first reply. Keep policy language out unless the client raises it.
- Lead by acknowledging the closing-tomorrow timing
- Don't re-ask for wire details, they're in the case file
- Offer human escalation in your first reply
- Reference the prior issues only if the customer raises them
- Avoid policy boilerplate
How Clara reads a customer message
We use nine different ways of understanding language, all grounded in research about how people actually communicate. Together they pick up what the customer really meant, what they felt, and what they didn't say.
Nine ways of reading a message
Big AI models jump straight from words to answer. Clara does the nine things in between that humans naturally do when they read a message. Each one is a small, specialized AI expert, grounded in research about how people actually communicate.
The reading step runs in a Google Cloud region in the United States today, and the record of what it did is written to Azure storage in the Canada East region. Your customer messages are not shared verbatim for model development, only a generalized form of the run, and you can switch that off at any time.
What the person is actually asking for, even when they don't say it directly.
Frustration, urgency, hesitation, hope. The mood behind the words.
Where the customer is in the workflow. What was said or done before.
The goal behind the question. Why they're asking, not just what they're asking.
Refund, complaint, technical question, escalation. Which playbook applies.
Your business rules, contract terms, and the norms that apply to this situation.
The laws and obligations your industry answers to. Not just your rules, the regulator's too.
How badly this could go wrong, for whom, and whether a person should look at it first.
Whether acting now is wise, and how much careful thought the answer deserves.
The nine readings come together into one short summary your AI can act on, plus a step-by-step record your compliance team can review. Better answers and safer answers, from the same pipeline.
Catch problems before the big AI is called
This is both a safety win and a money win. When a request should be blocked, we block it before any big AI is paid to run it.
Without Clara
- Customer message goes straight to a public AI service ($$$)
- The full message and any private data leave your network
- The answer comes back, maybe wrong, maybe risky
- Problems show up later, if at all
- Someone has to clean up, escalate, or explain to a regulator
With Clara
- Customer message read carefully before any big AI is involved
- You see the worst-case price up front, held as credits
- Answered, asked back, escalated, or blocked, with a clear summary
- The big AI only runs on approved requests, if at all
- Every step is written down, and unused credits are released
Quote, approve, run, get the summary
You see the worst-case price before any AI runs, and that amount is held up front. When the run finishes, you are charged only for what actually ran and the rest is released. If a request is blocked at the first check, the later steps never run and never charge. It's the up-front guarantee a buyer's finance team needs before they sign.
$ clara quote --workflow treasury_ops --action approve_transaction \
--amount 25000
Worst-case hold 4.2 credits (the most this run could cost)
Quote ID qte_8H2nKp
Expires 60s
$ clara authorize qte_8H2nKp
Credits held 4.2
Token aut_1ZqV3m
$ clara run --token aut_1ZqV3m
Step 1/4 Read the request ok (no big-AI calls yet)
Step 2/4 Understand the meaning ok (nine expert readings)
Step 3/4 Check the rules ok (policy + risk gates)
Step 4/4 Final review ok (independent judges)
Decision escalate
Reason amount above this user's approval limit
Record ID vrf_3mK8pNx
Charged 3.9 credits (0.3 unused credits released back)
$ clara brief vrf_3mK8pNx
Returns the full plain-English summary and the record of every step,
ready for your security or compliance log.The governed tier runs in Azure Canada East; the models it calls run on Microsoft global infrastructure, which can process a request outside Canada. A dedicated or isolated setup is available for enterprise. Cloudflare provides the secure edge (DNS, protection, and hosting for this site). First pilot committed with TicketWindow.ca. Research partnerships with Lambton and Fanshawe Colleges.
Get involved before public launch
Clara isn't open to the public yet. The two ways to get involved today are as a pilot customer or as a partner who can help shape the platform.
Pilot customer
Already have a use case where better AI answers and a complete paper trail would matter? Tell us about it.
Talk about a pilotPartner with us
Bring your industry, integration, or research expertise and we'll bake it into the platform from day one.
See partner programReady to add Clara?
Talk to us about a pilot, or look into the partner program.