Aureon Digital

How Orynth re-architected Aureon’s inbound funnel with a resilient AI qualification layer that filters noise and routes high-intent prospects straight to advisers.

//Automation Timeline

6 Weeks

//Industry

Financial Services

//Company Size

250 Employees

Case image

//The Challenge

We began with a full resilience audit of Aureon’s inbound journey, mapping every entry point, drop-off and manual handoff against regulatory and compliance constraints unique to financial services. From this we defined deterministic qualification logic and conversation guardrails, so the system behaves predictably under load and never routes a prospect on incomplete data.

//Strategy

Orynth engineered a conversational AI layer tightly coupled to Aureon’s CRM and booking stack. Every interaction is logged, validated against qualification criteria and only escalated to an adviser when confidence thresholds are met. Fail-safes and fallback paths were built in from day one, so a degraded model response never blocks a genuine lead.

//Execution

We rolled the system out behind staged traffic splits, monitoring response quality, handoff accuracy and adviser load in real time. Each iteration tightened thresholds and refined escalation triggers using live interaction data, until the qualification layer ran reliably without manual supervision.

//Metrix

//Work Reduction

3x

//Leads Growth

62%

//Response Speed

41%

//Monthly Cost Savings

28%

Aureon Digital

How Orynth re-architected Aureon’s inbound funnel with a resilient AI qualification layer that filters noise and routes high-intent prospects straight to advisers.

//Automation Timeline

6 Weeks

//Industry

Financial Services

//Company Size

250 Employees

Case image

//The Challenge

We began with a full resilience audit of Aureon’s inbound journey, mapping every entry point, drop-off and manual handoff against regulatory and compliance constraints unique to financial services. From this we defined deterministic qualification logic and conversation guardrails, so the system behaves predictably under load and never routes a prospect on incomplete data.

//Strategy

Orynth engineered a conversational AI layer tightly coupled to Aureon’s CRM and booking stack. Every interaction is logged, validated against qualification criteria and only escalated to an adviser when confidence thresholds are met. Fail-safes and fallback paths were built in from day one, so a degraded model response never blocks a genuine lead.

//Execution

We rolled the system out behind staged traffic splits, monitoring response quality, handoff accuracy and adviser load in real time. Each iteration tightened thresholds and refined escalation triggers using live interaction data, until the qualification layer ran reliably without manual supervision.

//Metrix

//Work Reduction

3x

//Leads Growth

62%

//Response Speed

41%

//Monthly Cost Savings

28%

Aureon Digital

How Orynth re-architected Aureon’s inbound funnel with a resilient AI qualification layer that filters noise and routes high-intent prospects straight to advisers.

//Automation Timeline

6 Weeks

//Industry

Financial Services

//Company Size

250 Employees

Case image

//The Challenge

We began with a full resilience audit of Aureon’s inbound journey, mapping every entry point, drop-off and manual handoff against regulatory and compliance constraints unique to financial services. From this we defined deterministic qualification logic and conversation guardrails, so the system behaves predictably under load and never routes a prospect on incomplete data.

//Strategy

Orynth engineered a conversational AI layer tightly coupled to Aureon’s CRM and booking stack. Every interaction is logged, validated against qualification criteria and only escalated to an adviser when confidence thresholds are met. Fail-safes and fallback paths were built in from day one, so a degraded model response never blocks a genuine lead.

//Execution

We rolled the system out behind staged traffic splits, monitoring response quality, handoff accuracy and adviser load in real time. Each iteration tightened thresholds and refined escalation triggers using live interaction data, until the qualification layer ran reliably without manual supervision.

//Metrix

//Work Reduction

3x

//Leads Growth

62%

//Response Speed

41%

//Monthly Cost Savings

28%