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PP Mobius - Tavistock Protect

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Tavistock Protect is one of the UK's fastest-growing mortgage and protection insurance specialists, operating as part of the Tavistock Investments Group - a group with 400 advisers, 80,000 clients, and over £5bn under management. The firm offers whole-of-market access across life and critical illness cover, income protection, mortgage products, private medical insurance, sports and hazardous pursuits cover, and commercial insurance. Tavistock Protect advisers operate under FCA-regulated expectations around advice suitability, documentation, and compliance oversight.

PP Mobius is the operational platform that makes that business run. It manages the complete lifecycle of protection sales - from client onboarding and fact finding through provider quote comparison, product recommendation, compliance review, AML checking, policy submission, commission calculation, payslip generation, and finance reporting.

Full-stack Development
AI Engineering
UX Design
Product Management
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Scope:

Dedicated Agile Team


Team:

4 People


Duration:

2+ years (ongoing)

Challenge

Protection insurance sales are operationally complex. The advice process involves collecting structured client information, comparing products across multiple providers, generating suitability recommendations, obtaining compliance sign-off, managing policy applications, and reconciling premium payments - all while operating under FCA requirements for documentation, traceability, and auditability.

Without a purpose-built operational system, those workflows tend to fragment. Client data lives in one tool, quotes come from a separate quoting platform, compliance review happens across email threads and spreadsheets, commission calculations are done manually, and finance teams reconcile payouts from downloaded exports. The result is inconsistent records, weak audit trails, manual intervention at every stage, and a compliance posture that is difficult to defend under scrutiny.

At the scale Tavistock Protect operates - hundreds of advisers generating sales across six product lines, commissions calculated and paid weekly, bi-annual bonus cycles running across a management hierarchy - the cost of fragmentation compounds quickly. Tavistock Protect needed a platform that did more than manage contacts. They needed a system that structured and controlled the entire advisory and finance operation: one where workflows were enforced, financial calculations were deterministic and explainable, compliance decisions were traceable, and every material action left an immutable record.

 

Solution

Redberry built PP Mobius as a single Laravel and Livewire platform covering the complete protection sales lifecycle, designed from the outset for an FCA-regulated operational environment. The system serves multiple internal teams - advisers, compliance reviewers, finance, and management - each with their own workflows, permissions, and views into the same underlying operational data. 

The architecture reflects the demands of regulated financial operations: state-gated workflows prevent users from bypassing compliance steps, a deterministic commission engine produces explainable outputs that can be audited and compared against prior logic, AI-assisted compliance checks automate the most repetitive review tasks while preserving the human oversight the regulatory context requires, and every significant action is logged against an immutable audit trail.

Rather than integrating existing tools at the surface level, Redberry built deep workflow integrations - with iPipeline SolutionBuilder for provider quoting, SmartSearch for AML verification, and Intelliflo for plan and client syncing - treating each as a core operational layer rather than an add-on. The platform runs on Laravel Cloud, giving Tavistock Protect the managed infrastructure and operational consistency a regulated production environment demands.

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Client Management and Structured Fact Find

At the foundation of PP Mobius is a structured client management and fact find system. Every client record is built around a comprehensive fact find that captures the full picture required for regulated protection advice: personal details, employment status, income, health information, dependents, expenditure, and existing cover. The fact find is not a static form - it drives the entire downstream workflow. Quote eligibility, compliance checks, AML verification, and recommendation generation all depend on what is captured here and when.

The system enforces completeness before key actions are permitted. An adviser cannot generate a quote without the relevant fact find sections being in place. When a client's circumstances change and a fact find is updated, the platform tracks exactly what changed, propagates those changes into the compliance workflow, and determines whether a fresh AML check is required. The fact find is both the evidentiary record that supports advice suitability and the operational trigger for everything that follows.

 



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End-to-End Quote-to-Policy Lifecycle

The core adviser workflow in PP Mobius takes a client from initial fact find through to a submitted protection policy without leaving the platform. The journey begins with an integrated connection to iPipeline SolutionBuilder - the UK protection insurance market's primary quoting platform. Fact find data is sent directly to iPipeline, eliminating manual re-entry, and the adviser creates and flags quotes there before returning to PP Mobius to retrieve them. Selected quotes are loaded into a structured slide-over where the adviser confirms the quote and generates a recommendation pre-populated with the relevant policy details: plan owner, cover type, policy type, sum assured, monthly premium, term, and product-specific fields.

Supporting documents are automatically saved into organised filesystem structures within the platform. The recommendation then moves into compliance submission, through compliance review and client signing, and finally to policy application: once compliance has approved and all client signatures are confirmed, the Apply button activates and redirects the adviser directly to the provider's portal. The entire journey - sourcing a quote, creating a recommendation, clearing compliance, and submitting the policy - is tracked, auditable, and contained within a single system.

 



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Compliance Review and Approval Workflow

PP Mobius treats compliance not as a final checkpoint but as a structured operational layer embedded throughout the sales process. Once an adviser submits a fact find, a compliance case is opened and moves through a defined status lifecycle. Status gating means advisers cannot advance the case - generating quotes, creating recommendations, obtaining client signatures, or applying for policies - until compliance milestones are met.

Compliance reviewers work from a dedicated view of each case that gives them full visibility into the fact find data, the recommendation, supporting documents, and the AML check outcome. They can record structured notes, request rework from the adviser, and track what changed between submissions.

AML verification is embedded directly into the submission workflow through an integration with SmartSearch. The result appears immediately in the compliance view alongside a full AML history tab that retains every check performed across the life of the case, timestamped and permanently retained. Change-detection logic on resubmission means a new SmartSearch call only fires if identity fields have actually changed - preventing unnecessary external checks while keeping the compliance record accurate.

 



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AI-Powered Compliance Check Automation

Beyond the human compliance review workflow, PP Mobius includes an automated compliance check engine built on Laravel AI SDK. When a fact find is submitted, the system automatically initialises a structured compliance checklist containing three types of assessment: system checks driven by deterministic business rules, AI checks where individual micro-agents analyse the fact find independently and return results with confidence scoring and trace outputs, and manual checks that require a compliance reviewer to assess and record a decision.

The system supports full versioning of compliance reviews. Compliance can create a new version, selectively re-running automated checks and resetting manual ones, without losing the historical record of prior versions. Every version is a read-only, immutable snapshot with its own isolated activity log. The entire review - any version - exports as a structured PDF designed for FCA audit defensibility, with version number, check statuses, notes, and confidence levels included.

 



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Deterministic Commission Engine

Commission calculation is one of the most complex and audit-sensitive parts of PP Mobius. The platform calculates adviser payouts across a multi-tier structure, resolving product type, sale classification, exception conditions, and each adviser's monthly production position into a single auditable output - consistently, without manual intervention.

The commission calculation engine works simultaneously across multiple layers of Tavistock Protect’s organizational hierarchy - advisers, team leaders, area managers, senior managers, regional managers, etc. - each carrying their own rate structures, override entitlements, and access-level-dependent rules. A sale classified one way generates a different financial outcome depending on who made it, under which product access level, and where it sits within the exception hierarchy. Tier thresholds, production ranges, per-product rates, in-house sale rates, and override structures by management level are all configurable by administrators through the platform, so the engine reflects the current business rules without requiring a development change.

The engine is designed to be correct first, auditable second, and changeable without risk.

 



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Finance Operations: Bonuses, Payslips, and Reporting

With commissions calculated, PP Mobius handles the full downstream financial operation. Payslips are generated in bulk across the entire adviser base. The system lets finance team select a pay period, preview all sales and their formatted commission outputs across the full adviser population, and trigger background generation for every participating employee simultaneously.

Beyond regular commissions, the platform calculates multiple categories of bonuses for management-tier employees: recruitment bonuses based on new advisers reaching defined production tiers, live business bonuses based on team output with cancellation-rate adjustments, persistency rate bonuses tied to team-level policy retention, traffic light status bonuses rewarding consistent adviser performance, promotion bonuses for advisers elevated into management, and introducer arrangement bonuses for advisers who refer recruits that meet qualification criteria. Each bonus type has its own eligibility rules, penalty thresholds, and automated calculation service.

 

Involvement & Process

The backend of PP Mobius is one of the most rule-dense Laravel systems Redberry has built. It manages client records, fact finds, recommendation lifecycles, compliance state machines, AML integration, commission calculations, bonus logic, payslip generation, Intelliflo synchronisation, and finance reporting - all within an operational model where incorrect calculations or broken audit trails carry material consequences.

The commission and bonus engines required particular care. Rolling YP calculations, tier assignment logic, in-house sale hierarchies, exception precedence rules, and bi-annual bonus formulas each carry their own edge cases, many of which interact with each other. The compliance workflow layer introduced a different kind of complexity: version management, immutable audit records, change-detection logic for AML re-triggers, and the coordination of system, AI, and manual check states across a branching review lifecycle.

The AI-powered compliance check system is built on Laravel AI SDK. Each compliance check type is implemented as a discrete checkable class conforming to a shared interface, making the system extensible as new check types are introduced. When a compliance check is initiated, the system dispatches individual micro-agents per check - each running independently in the queue with its own execution trace and confidence assessment. A final aggregation agent synthesises individual results into an overall compliance summary.

The architecture ensures AI checks don't block the UI: results stream to the frontend as they complete, so compliance reviewers see the checklist come to life in real time. Evidence items, reasoning steps, trace outputs, and confidence levels are stored against each check result, giving compliance teams and auditors full visibility into how each AI assessment was reached.

The frontend is built with Laravel Livewire, enabling reactive interfaces that update in real time without full page reloads. The compliance review page is the clearest example: check statuses, progress counters, and AI results update live as agents complete their work. The iPipeline slide-over, the flagged quotes interface, the replace recommendation flow, and the AML history tab are all Livewire-driven components that surface complex backend state in a clear, role-appropriate way.

The admin and manager experience covers a wide operational surface: adviser profile management, commission tier and rate configuration, access level assignment, bulk actions across client and sales lists, report generation, and payslip management - each with its own permission model and workflow context.

The platform runs on Laravel Cloud, providing managed infrastructure appropriate for a regulated production system handling sensitive financial and personal data. CI/CD pipelines keep development, staging, and production environments consistent. Deployment processes are governed to match the operational caution the regulated environment and weekly payslip cycle require.

Tech Stack

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