Case study

2026AI

AI agent trust layer

Your AI agents worked all night. Can you prove a single action was right?

Companies plugged AI agents into their CRM. Almost none could see what those agents touched, why, or what it cost. We built the trust layer that checks every agent action before it reaches a customer.

Client: Yexoria product
Year: 2026
Services: AI engineering · Product design
Platform: Salesforce, HubSpot, Zendesk, web & mobile

Agent decision log marking actions as approved, held for review or blocked, beside an agent trust score

The problem

AI agents act on duplicate records, run on an admin login, and nobody sees the token bill until month end.

One agent action, start to finish

What happens in the second before an agent acts

One agent action, start to finish

What happens in the second before an agent acts

01 / 05 · THE REQUEST

An agent wants to act.

The outreach agent wants to email 58 contacts about a webinar. Before the trust layer, it just sent them.

Outreach Writer · HubSpotsend_email × 58
Requested 09:38:12checking

02 / 05 · DATA CHECK

Is the data true?

Every contact gets a trust score for freshness, duplicates and missing fields. 12 of the 58 fail.

Ananya M. · verified this monthTrust 96
R. Kapoor · duplicate recordTrust 31
S. Lane · unsubscribed in MarchTrust 12
David N. · no company on fileTrust 48

03 / 05 · SCOPE & BUDGET

Is it allowed, and affordable?

The agent gets a key that covers only this send, for 90 seconds. The cost is checked against its daily cap.

1Key for 46 sends
2Valid 90 seconds
3$94 of $150 cap
4Within budget

04 / 05 · THE DECISION

Approve, review or block.

Safe actions go through on their own. Risky ones wait for a person. Bad ones never happen.

46 trusted contactsSent
12 low-trust contactsHeld back
20% discount offerNeeds approval

05 / 05 · THE RECORD

Logged, and one click to undo.

Which agent, which data, which rule and who approved it. If anything was wrong, the whole run rolls back.

“Undo everything Renewal Nudger did after 9 am.”

request

logged

●Under the hood

Four checks before, four controls after

LANE A · BEFORE THE ACTIONLANE B · AFTER THE ACTION ←

A1Data Trust Score

A2Earned Autonomy

A3Scoped Permissions

A4Cost per Outcome

B1Review Queue

B2Audit Trail

B3One-click Rollback

B4Mobile Kill Switch

node 1 / 8

Data Trust Score

Each record gets a live score for freshness, duplicates and missing fields.

solves → Agents treating stale records as truth.

↺ Every approved or rejected action trains the next decision

The product

Watch every agent from your desk. Stop one from your phone.

Leaders see outcomes and cost on the big screen. Managers approve risky actions on a tablet. Anyone on the go gets the alert and can pause an agent in one tap. Try the buttons.

Trust Layer · OverviewSAMPLE DATA

Good morning, Priya

Thu 22 Oct · 4 agents live · synced 12s ago

Trust score87▲ 6 this week

Actions today4,812100% traced

Bad-data stops265$48.2K protected

AI spend · Oct$8,42070% of $12K cap

Actions by hour today

Approved 3,906Review 641Blocked 265

Spend vs cap October

Spend to dateCap $12,000

Agents 4 live

Agent	Trust	Autonomy	Cost / outcome	Today	Status
Support Resolver · Zendesk	94	L3 · auto	$0.42 / ticket	$61	healthy
Pipeline Updater · Salesforce	91	L3 · auto	$0.08 / update	$22	healthy
Outreach Writer · HubSpot	78	L2 · risky reviewed	$3.10 / meeting	$94	learning
Renewal Nudger · Salesforce	62	L1 · supervised	$11.80 / renewal	$212	cost spike

Recent decisions live

blockedPipeline Updater tried to close a deal from a duplicate record (trust 34)09:41

reviewOutreach Writer drafted a 20% discount. Sent to Ravi for approval09:38

rolled back72 contact updates from Renewal Nudger undone by Priya09:20

Trust score, actions, bad-data stops, revenue protected, spend vs cap, cost per outcome and live decisions.

Scroll to switch the system on

BEFORE

Agents acted. Nobody checked.

✕Agents read duplicate and outdated records as truth.
✕Every agent ran on a human's login with full access.
✕AI cost showed up on the invoice, weeks later.
✕Mistakes were found by customers and fixed by hand.

AFTER YEXORIA

Every action checked first.

✓Low-trust records are held back before an agent touches them.
✓Each action gets a key for that task only.
✓Spend per outcome is live, with hard caps.
✓Any agent run can be paused from a phone and undone in one click.

Impact

Why teams switch it on

70%failure rate of AI agents on complex sales tasks, mostly from bad CRM dataindustry research · Strama AI

8 checkson every agent action, before and aftersystem design

Every actionlogged with agent, data, rule and approversystem capability

1 tapto pause any agent from a phonesystem capability

OUTCOME 1

Agents stop acting on records nobody would trust.

OUTCOME 2

A runaway agent costs minutes of spend, not a month.

OUTCOME 3

When compliance asks what the AI did, the answer is one screen away.

Could this work for you?

Built for any team where an AI agent touches customer records

B2B SaaS sales

Pipeline updates, follow-ups and renewals without deals closed from duplicates.

Banking & lending

Lead qualification and offers with a full audit trail for regulators.

Insurance

Claims and renewal reminders approved only on current policy data.

Healthcare

Scheduling and billing agents that see only what each task needs.

E-commerce & D2C

Refunds and win-back campaigns with hard spend caps.

Real estate

Enquiry follow-ups that skip old leads and outdated prices.

Telecom

Plan changes and retention offers that can be undone in bulk.

EdTech

Counselling and fee reminders that respect every unsubscribe.

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