Overview
All AI features available in the Legistify platform are powered by Large Language Models (LLMs) accessed through AWS Bedrock. These models operate entirely within our secure AWS cloud infrastructure, ensuring that AI capabilities are delivered while maintaining strong data protection and regulatory compliance.
This architecture allows Legistify to provide advanced AI-powered capabilities such as contract analysis, drafting assistance, and document insights without exposing client data to external AI platforms.
Type of AI/ML Models Used
Legistify uses state-of-the-art Large Language Models (LLMs) available through AWS Bedrock.
These models are foundation models trained on large-scale and diverse datasets to support advanced natural language processing tasks such as:
Document understanding
Text generation
Legal drafting assistance
Contract analysis
Model outputs are guided through controlled prompt design and application-level logic to ensure the responses are relevant, consistent, and aligned with legal workflows.
Legistify does not build, host, or train custom AI models outside AWS Bedrock for these use cases.
Architecture & Deployment
All AI workloads run securely within Legistify’s AWS cloud environment.
Key architectural characteristics include:
AI requests are processed using AWS Bedrock APIs
All AI/ML workloads execute within Legistify’s AWS account
No direct integration with external or public AI platforms
Client data remains within Legistify’s AWS infrastructure throughout the processing lifecycle
This architecture ensures that AI capabilities remain fully integrated within Legistify’s secure platform environment.
Data Security & Privacy
Legistify follows strict security and privacy practices when processing data through AI features.
Data Usage & Retention
Client data is processed only for the specific AI request initiated by the user.
Key principles include:
AWS Bedrock does not store, reuse, or retain prompts or outputs
Client data is not used for training or improving foundation models
AI interactions are stateless and request-based
This ensures that client data remains private and is not reused beyond the immediate request.
Encryption
Legistify protects data both in transit and at rest.
Security controls include:
TLS encryption for data in transit
AWS-managed or customer-managed KMS keys for data at rest
These measures ensure that sensitive contract and legal data remains securely protected.
Access Controls
Strict access management policies are enforced across the platform.
Controls include:
Role-based access control (RBAC) using AWS IAM
Least-privilege access policies to restrict system access
Controlled access to AI resources and infrastructure
These mechanisms ensure that only authorised systems and personnel can interact with AI services.
Network Security
All AI interactions occur within a private and secure network environment.
Security measures include:
AI processing occurs inside a private AWS VPC
No public exposure of AI endpoints
Secure internal communication between services
This prevents unauthorised external access to AI services.
Conclusion
Legistify’s AI architecture is designed to deliver powerful AI capabilities while maintaining strict standards for security, privacy, and compliance.
By leveraging AWS Bedrock within a secure AWS infrastructure, Legistify ensures that AI-powered features can analyse documents, generate insights, and assist legal workflows without compromising the confidentiality of client data.
This architecture allows organisations to confidently use AI within the platform while maintaining full control over their data.