What makes the Flow framework different from standard chatbots?

Flow imposes structure on inherently unpredictable LLMs through state-based conversation maps. This ensures business processes complete successfully, data is collected reliably, and conversations can't be hijacked—critical for regulated industries like insurance and financial services.

How long does implementation really take?

Our standard implementation is 12 weeks for a production-ready system. The first 2 weeks focus on discovery and foundation, followed by 6 weeks of core development, and 4 weeks of testing and handover. You'll have access to a working system by week 9 for UAT.

Do we need to be on Azure?

Yes, our architecture is optimised for Azure's PaaS services. However, this is an advantage—you leverage existing Azure investments, security postures, and team expertise rather than introducing new platforms and vendors.

What about GDPR and the EU AI Act?

Compliance is built into our methodology. We establish governance frameworks aligned with ISO 42001 and ISO 27001, complete DPIAs, implement transparency notices, and ensure full regulatory compliance throughout the project.

How do you prevent AI hallucination?

Three ways: The Flow framework constrains conversations to defined paths, RAG provides grounded responses from your documents, and continuous monitoring detects and flags potential hallucinations for correction.

What happens after the 12-week project?

You own everything—the Flow framework licence, configured flows, aligned models, and all code. We provide comprehensive documentation and training. Optional managed services are available for ongoing optimisation and feature development.

State-Based Conversational AI That Actually Works

From Unpredictable Chatbots to Controlled Business Outcomes

Companies Assisted

PE Companies Served

CSAT

Practitioners hold an AI PhD

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Traditional LLMs are inherently unpredictable—a critical flaw for business processes. Our Flow framework brings structure and control to AI conversations, ensuring reliable data collection, accurate tool use, and consistent outcomes. Built on Azure, owned by you, delivered in 12 weeks.

Why Attercop for Conversational AI

Three fundamental advantages that make our approach different

The Attercop Flow Framework

Prevent Hijacking, Ensure Outcomes

Our proprietary Flow framework solves the fundamental problem of LLM unpredictability. By imposing state-based structure, we ensure conversations stay on-task and reach successful outcomes—essential for regulated processes like insurance claims.

Complete Ownership & Control

Your Platform, Your IP

Unlike vendor solutions that lock you into subscriptions, we deploy directly into your Azure tenant. You receive full, unencumbered licences for all components including our Flow framework—creating a strategic asset, not a liability.

Proven Enterprise Delivery

Built Like Financial Services Grade Systems

Drawing from our experience building Agentic Mesh platforms for global life sciences and financial services, we deliver reusable, governable AI infrastructure—not just chatbots.

Why Standard LLMs Fail in Business-Critical Processes

Without structure, users can divert AI assistants into off-topic discussions from which they cannot recover. In regulated industries like insurance, this creates unacceptable risks.

Traditional Chatbot

Unpredictable conversation paths
Incomplete data collection
Unreliable tool execution
No guaranteed outcomes
Vulnerable to prompt injection

Flow-Controlled AI

Defined state machines
Enforced data collection
Reliable tool orchestration
Guaranteed process completion
Inherent security through structure

Flow Framework Architecture

State-Based Conversation Maps

Each conversation follows a definitive map with clear states, transitions, and outcomes. The AI cannot deviate from the designed flow, ensuring business processes complete successfully.

Reliable Data Collection

Each state specifies required data points. The system ensures all necessary information is gathered accurately before proceeding, eliminating the 'I forgot to ask' problem.

Deterministic Tool Use

API calls and system actions occur at designated states in the correct sequence. No more wondering if the AI will remember to update the CRM or submit the claim.

Built-in Recovery

When users go off-topic, the Flow framework guides them back to the task at hand, maintaining conversation continuity without losing context or progress.

Enterprise-Grade Architecture on Azure

Microservices architecture with containerisation and secure interoperability. All services deploy within your Azure subscription.

Azure Kubernetes Service

• Flow Execution Engine
• Tool Integration Layer
• Auto-scaling orchestration
• Zero-downtime deployments
• Distributed caching (Redis)

Multi-Channel Gateways

• Voice (Azure Communication Services)
• Web & Mobile (App Service)
• WhatsApp (Bot Service)
• Speech-to-text & TTS
• <2 second response target

Knowledge Engine (RAG)

• Azure AI Search
• Automatic document chunking
• Embedding generation
• Semantic search
• Citation-backed responses

Security & Compliance

Infrastructure Security

• Azure Key Vault with automated rotation
• VNet Peering/Private Link
• API gateway with rate limiting
• Container security policies

AI-Specific Protection

• Flow framework prevents prompt injection
• Azure AI Content Safety integration
• Voice anti-spoofing measures
• Input/output validation layer

Proven Applications Across Industries

Real-world implementations delivering measurable results

INSURANCE

First Notice of Loss (FNOL)

Challenge:

Complex claims process requiring accurate data collection

Solution:

Voice-driven FNOL with authentication, validation, and submission

Results:

24/7 claims acceptance
100% data accuracy
5-minute average completion
Zero manual data entry

FINANCIAL SERVICES

Customer Authentication

Challenge:

Regulatory compliance for voice-based authentication

Solution:

Multi-factor voice authentication with anti-spoofing

Results:

95% authentication success rate
Regulatory compliance achieved
Fraud attempts detected
Customer friction reduced

HEALTHCARE

Patient Triage

Challenge:

Overwhelming call volumes for appointment booking

Solution:

Intelligent triage and appointment scheduling

Results:

70% call deflection
Appropriate care routing
Reduced wait times
Clinical governance maintained

RETAIL

Order Management

Challenge:

High-volume customer service for order queries

Solution:

Automated order tracking and modification

Results:

80% query automation
Instant order updates
Customer satisfaction increased
Support costs reduced

12-Week Transformation: From Concept to Production

Fixed-price delivery with transparent outcomes and quality gates

Discovery & Foundation

Weeks 1-2

Requirements elaboration and backlog creation

API standardisation and OpenAPI specifications

Document standards for RAG implementation

AI Governance Framework establishment

Risk register and DPIA skeleton

Azure environment provisioned

Core Development & Integration

Weeks 3-8

CI/CD pipeline establishment

AKS cluster provisioning via Terraform

Flow Engine configuration

Tool Integration Layer development

Channel gateway implementation (Voice, Web, WhatsApp)

RAG implementation with Azure AI Search

Backend API integration

Testing & Handover

Weeks 9-12

Functional and integration testing

Performance and load testing

Security testing and threat modelling

AI evaluation (accuracy, hallucination, adversarial)

User Acceptance Testing support

Infrastructure as Code (Terraform)

Documentation and runbooks

Knowledge transfer and training

Investment Framework

Discovery

2 weeks

Requirements • API specs • Governance framework • Test strategy

Full Implementation

12 weeks

Complete Flow framework • Multi-channel • Full testing • Handover

Ongoing Evolution

Managed Services

Feature enhancements • Performance optimisation

Strategic AI Assets That Drive Exit Value

Why PE firms choose Flow-controlled conversational AI

Technology Asset Creation

Building conversational AI with full IP ownership creates a defensible technology moat. Unlike SaaS subscriptions that appear as OpEx liabilities, owned AI platforms are strategic assets that enhance enterprise value at exit.

Scalability Without Headcount

Deploy once, scale infinitely. Our platform approach enables rapid expansion without proportional increases in support staff—critical for PE firms focused on EBITDA margin expansion.

Cross-Portfolio Leverage

The Flow framework and governance models developed for one portfolio company can be adapted across others, creating economies of scale and accelerating subsequent deployments.

Regulatory Readiness

With built-in compliance for GDPR, EU AI Act, and sector-specific regulations, portfolio companies are prepared for increasingly stringent AI governance requirements—removing a potential exit barrier.

Frequently Asked Questions

Complementary Services

Extend your conversational AI capabilities

Knowledge Engineering

Build the intelligent foundation that powers meaningful conversations with deep business understanding and RAG implementation.

Explore Knowledge Engineering

Agentic AI

Extend beyond conversations to autonomous agents that take action across your enterprise using our Agentic Mesh architecture.

Discover Agentic AI

AI Governance

Ensure your conversational AI meets compliance, ethical, and control requirements with our ISO-aligned governance framework.

Learn About Governance

Ready to Control Your AI Conversations?

Discover how the Flow framework can transform unpredictable LLMs into reliable business systems.

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