Listen. Connect. Understand. Assure. Improve.
Five stages take a customer interaction from what was said to what outcome the customer received - and what to do about it. The same engine runs every use case.
From what was said to what the customer received.
- 01
Listen
Capture connected customer interactions.
Voice, chat, email and digital interactions - human and AI-led - are captured and transcribed across every channel you connect, not sampled.
- 02
Connect
Combine interactions with CRM and journey evidence.
Each interaction is assembled with the customer record, earlier contacts, commitments and follow-ups so the outcome can be judged in context.
- 03
Understand
Use AI to assess what happened and why.
AI reasoning sets out what was said and done against the evidence, with a confidence level and the source it relied on.
- 04
Assure
Evaluate against configured customer outcome criteria.
Your outcome frameworks and scorecards are applied consistently; reviewers confirm, reject or override with a recorded rationale.
- 05
Improve
Turn insight into coaching, remediation and operational action.
Root causes, trends and coaching priorities are reported with drill-down to evidence, and outcomes are tracked after the change.
From flagged interaction to confirmed customer outcome.
Five steps, one evidence trail. Each screen below shows what the reviewer, operations lead or compliance team sees at that point in the journey.
Step 01 · Customer outcome dashboard
AI identifies a potential poor customer outcome
Every connected interaction is assessed against your outcome framework. Where the evidence suggests the customer may not have received the right outcome, the section or journey is surfaced for attention.
- Pass rate by journey stage across every evaluated interaction
- Weak stages - here Documentation at 51% - flagged for review
Step 02 · Individual customer journey
Interaction, CRM and customer journey evidence is assembled
The call, chat or email is placed alongside the CRM record, earlier contacts and operational events, so the reviewer sees the whole journey rather than a single conversation.
- Timeline of every contact across channels
- CRM and case events linked to each interaction
- 12 Mar
- Inbound call - payment difficulty disclosed
- 12 Mar
- CRM: affordability review scheduled
- 19 Mar
- Email - customer chases outcome
- 26 Mar
- No follow-up recorded
Step 03 · AI assessment and supporting evidence
Better Outcomes explains why the outcome has been flagged
Each finding sets out the AI reasoning, the source evidence relied on and a confidence level. Nothing is a bare score - the reviewer can see exactly what the conclusion rests on.
- AI reasoning shown beside the verbatim source evidence
- Confidence level on every finding
Step 04 · Human review
A human reviewer confirms, rejects or investigates
Reviewers inspect the evidence, record their decision and rationale, and can override the finding. Every decision becomes part of the audit history.
- Confirm, reject or escalate with recorded rationale
- Override history retained for calibration
- Reviewer
- S. Patel · Quality lead
- Decision
- Confirmed - customer harm likely
- Rationale
- Commitment made on call not actioned; customer chased twice
- Escalation
- Routed to Consumer Support remediation queue
Step 05 · Trends, root cause and management insight
Coaching, action and management insight follow
Confirmed findings feed root-cause analysis, targeted coaching for advisers and trend reporting for leadership and compliance - with human–AI evaluation agreement tracked alongside.
- Overall score, completed reviews and human–AI evaluation agreement at a glance
- Root-cause assessment identifies systemic failures, not just individual errors
Shown with test data. The in-product “AI evaluation accuracy” tile is human–AI evaluation agreement: the share of completed human reviews in which the reviewer agreed with the AI-generated evaluation. Reviewers could see the AI assessment when making their decision. The published live figure is on the Results page.
Different questions. The same Better Outcomes engine.
Whatever the use case, Better Outcomes applies the same core approach.
- Interaction evidence
- Customer and CRM data
- Journey context
- Configurable outcome criteria
- AI reasoning
- Human review
Clearer evidence of the outcomes customers receive.
Real Better Outcomes screens · Shown with test data
AI you can evidence, not just trust.
The AI does not simply generate a score. It produces an assessment that a reviewer can check against the evidence used to reach it - and change if the evidence does not support it.
Your data
Customer data is never used to train public or shared AI models. Any model tuning is opt-in and used only for that customer. Products are hosted on UK infrastructure with access segregated by organisation, team and user.
Security and governance/ 01
Configurable outcome frameworks
Your outcome definitions, scorecards and rules - applied consistently across every connected interaction.
/ 02
Evidence behind every assessment
Each finding links to the interaction, CRM record and journey events it was drawn from.
/ 03
Explainable reasoning
The criteria applied and the reasoning followed are shown beside the evidence, not hidden in a score.
/ 04
Human-in-the-loop review
Reviewers confirm, reject, escalate or override - with authority to change the outcome and a recorded rationale.
/ 05
Confidence thresholds
Where applicable, low-confidence findings route to human review before any action is taken.
/ 06
Audit history
Findings, decisions, overrides and model versions are written to an append-only audit history.
/ 07
Configurable escalation
Route confirmed findings to remediation, coaching or compliance queues according to your governance model.
/ 08
Role-based access
Named permissions by organisation, team and role, with MFA and lifecycle management.
/ 09
Reporting and governance
Trend, calibration and override reporting for quality, operations, risk and Board oversight.
/ 10
Data controls
UK product hosting, tenant segregation and defined data scope agreed per deployment.
From your customer journeys to a configured deployment.
Start with a focused pilot. We agree your onboarding timetable around your systems, customer journeys and assurance requirements.
Timings depend on integration scope, data readiness, security approvals and customer availability. We agree the deployment timetable during scoping.
- Step 1.
Scope
Sequential · comes first
Agree the customer journeys, desired outcomes, success measures, data scope and responsibilities.
- Step 2.
Connect
Can overlap with configure and calibrate
Connect the agreed interaction and CRM evidence sources, and validate customer and case matching.
- Step 3.
Configure and calibrate
Can overlap with connect
Configure outcome criteria and review workflows. Compare assessments with human reviews and investigate disagreements.
- Step 4.
Pilot and launch
Sequential · after calibration sign-off
Run a controlled pilot, train reviewers, agree acceptance criteria and provide support through launch.
What your team provides
- A business and technical owner
- Representative journeys and approved outcome criteria
- Access to agreed data sources
- Reviewers for calibration and sign-off
What we agree together
- Integration scope and responsibilities
- Data handling and access requirements
- Pilot success measures
- Acceptance criteria and launch timetable
Preparing for your session? See what to bring.
See Better Outcomes on your customer journey.
Bring one representative customer journey and we'll show how Better Outcomes could assess it across interactions, CRM evidence and customer outcomes. No customer data is required for the first session.