AntaraInnovations

Solutions · compliance, governance, consulting

Your people are already using AI. Nobody can say where.

The tools got into the building before the rules did. We find them, test what they can cause, and put a named person in charge. Read-only, and tuned to your regulator.

Discuss a deployment → Open the live console
  • Read-only access
  • First result in two weeks
  • Nothing to install

What is happening right now

Four sentences we hear in almost every first meeting.

Composites from conversations, not quotes from named clients. If one of them sounds like your week, you are not behind. You are normal.

01Half the team uses some AI tool. I could not give you a list.

Browser extensions, free chatbots, note-takers on personal accounts. It arrived one convenient shortcut at a time, and nobody decided it.

Soundings looks for it
02We gave an agent access to make life easier. What can it actually do?

Most agents get set up for what they should do. Very few get tested for what they could do on a bad day.

Sentinel tests it
03If the regulator asks who is accountable for this, who do I name?

Under SM&CR and FINMA, a shrug is not an answer. Somebody has to own each use of AI, by name.

Keel assigns it
04The AI got it wrong and my team did not notice.

This is the one people go quiet about. The tool is rarely the whole problem. Tired, busy people trust a confident answer.

The free instruments test this

Our answer

Governed AI that works inside your organisation. Three agents look, a person decides.

Each one reads your environment, investigates and files a report. Nothing changes until someone with a name approves it.

01 / SEERead-only

Soundings

Finds the AI already running in your organisation.

Reads files exported from your systems, on one machine. Nothing leaves your firm.

Unregistered Open Soundings →
02 / TESTRead-only

Sentinel

Tests what your AI agents can actually cause.

Follows each agent from what it can touch to what it could set off, and marks where a person has to be in the loop.

Agent Action Effect Person in the loop Open Sentinel →
03 / GOVERNRead-only

Keel

Governs how AI gets approved and who answers for it.

A named accountable person for every AI use, mapped to SM&CR and FINMA expectations.

Named owner approves Open Keel →

How honest the output is

Every finding says how sure we are.

Each finding is marked observed, declared, inferred or unknown. A guess never gets dressed up as a fact, and if nobody owns an AI tool yet, the finding says so.

Seen directly in the files we were given.

Soundings · finding01
tool Meeting-notes assistant
seen in Browser extension export
status OBSERVED
owner none recorded
data leaves UNKNOWN
next Name an accountable person

The method

Every AI action passes six questions.

  1. 01

    Identity

    Who is acting? A human, an AI agent, or a shared and delegated login. We establish who, for every action.

  2. 02

    Authority

    What may it do? Least privilege by design, with approval workflows for anything above the limit.

  3. 03

    Context

    What does it use? The data it reads, the outside information it trusts, and how good that data is.

  4. 04

    Action

    What can it cause? Read, write, execute, or trigger other agents. A person stays in the loop where it matters.

  5. 05

    Evidence

    Can we reconstruct it? Inputs, outputs and the approver, in a record that cannot be quietly edited.

  6. 06

    Adaptation

    What should change? Near-misses become control recommendations, and they go back to the start.

What we learn goes back into the rules refund £2,400
Who is acting?Flag

claims-agent-07, running on a shared login. Nobody can say which person started it.

Real-life cases

Not a theory. Four engagements at large global firms.

Financial crime, credit decisioning, enterprise machine learning and real-time fraud. Led by Abhinav Gaurav.

Read the real-life cases →

Antara and the alternatives

Most AI tools watch the technology. We answer the questions a board asks.

The questionAntaraMost platforms
Who answers for each AI use?
A named accountable person for every use, mapped to SM&CR and FINMA.
A dashboard of tools with a risk score.
Do your people catch the failures?
A measured judgement test: accuracy and confidence when the AI gets it wrong.
Tests the model. Never the people.
How long to a first result?
Two weeks. Nothing to install, no integration project.
Months of integration and a licence.
Whose rules come first?
UK and Swiss: SM&CR, Consumer Duty, FINMA.
Built around the EU AI Act, NIST and ISO.
Can you trust the advice?
We have no platform of our own to sell.
Recommends its own product.

Book a scoping call →Read the real-life cases →

Free instruments

Four short tests. Each one tests you.

No account needed. They measure what you do under pressure, and never ask how confident you feel.

Financial servicesBearing AI regulatory readinessFour written answers, graded against what the regulator says good evidence looks like. Free Banking and insuranceSquall Judgement under pressureSix scenarios, 25 seconds each. Call each one genuine, fake, or escalate it. Free Agencies and marketingEnsign AI disclosure readinessSix timed scenarios and one written answer on when AI-made content needs a label. Free LeadersHALO Your own practice, with AI in the roomA conversation with an AI interviewer who asks for specific, recent examples. Free

One company, one idea

The same question sits in three places.

In the organisationWho is accountable when AI acts? That is this page. In the personWhat does living next to intelligent machines do to us? That is Antara Wellness. In the clinicHow does a specialist stay in charge of what the AI sees? That is Pulse.

Fifteen minutes to scope it.

Book a scoping call → or write to hello@antara-innovations.com