Transforming Contract Lifecycle Management With Serverless AWS Architecture
Driving secure, automated contract workflows with intelligent lifecycle orchestration on a scalable AWS serverless foundation
30% Faster contract processing
through automated workflow orchestration and lifecycle tracking
40% Reduction in operational costs
achieved using serverless architecture and reduced infrastructure overhead
About the Client
A LegalTech company offering a unified platform to manage, sign, and store contracts. Through intelligent workflows, customizable templates, digital signatures, and centralized repositories, it streamlines legal document management and improves operational efficiency for startups and SMEs.
Industry
LegalTech
Years in business
3+ years
Employee count
10+
Presence
India
“Forgeahead helped us modernize our cloud infrastructure in a way that improved scalability, reliability, and overall efficiency for our research platform.”
Dr. Michael Harrington
Chief Information Officer
the need
The client, a digital financial solutions provider, aimed to extend its platform capabilities to support end-to-end contract lifecycle management for startups and SMEs across global markets. The goal was to unify contract creation, approvals, signatures, and storage within a single digital ecosystem.
Existing workflows were heavily manual and lacked automation, leading to delays in approvals, inconsistent document handling, and limited operational efficiency. As usage increased, the system struggled to scale while maintaining performance and reliability.
Security and compliance requirements were strict due to the sensitive nature of legal documents. The platform needed to support secure authentication, multiple signing methods, and controlled access while ensuring a seamless user experience across web and mobile channels.
In addition, the client required a flexible architecture that could support third-party integrations, intelligent document handling, and future AI-driven enhancements without impacting system stability.
the solution
Forgeahead implemented a secure authentication layer using AWS Cognito and AWS SNS, enabling OTP-based login flows that strengthened identity verification while ensuring smooth onboarding across devices.
A fully event-driven contract lifecycle system was designed using AWS Lambda, enabling automated transitions between contract stages such as creation, review, signing, and archival. This eliminated manual coordination and improved operational flow efficiency.
A rich document interaction layer was developed with drag-and-drop signature placement, dynamic field controls, and a flexible text editor. This empowered users to design and customize contracts with precision and reduced dependency on static templates.
Machine learning–based document classification was introduced to automatically categorize contracts based on structure and content patterns. This improved document retrieval speed and reduced manual sorting effort across large datasets.
Advanced collaboration features were implemented, including folder-based organization, real-time commenting, and secure sharing. These capabilities improved teamwork efficiency and ensured smoother contract review cycles across stakeholders.
A contract intelligence dashboard was built to surface actionable insights such as contract status trends, lifecycle bottlenecks, and usage behavior, enabling better decision-making and visibility across the platform.
The Impact
99.9% System Availability
The platform ensured uninterrupted access and reliable contract processing for users across global regions.
70% Faster Release Cycles
Deployment velocity improved significantly through automated serverless pipelines with minimal manual intervention.
30% Reduction in Processing Time
Contract workflows became more efficient through automated lifecycle orchestration and streamlined processing logic.
25% Improvement in Compliance Efficiency
Regulatory adherence improved through automated alerts for renewals and contract expiry tracking.
40% Lower Infrastructure Costs
Operational expenses were reduced through pay-per-use serverless execution and minimized infrastructure maintenance overhead.
Improved Operational Scalability
The system dynamically handled fluctuating workloads without any degradation in performance or responsiveness.
Role of AWS
AWS provided the serverless foundation that enabled scalable, secure, and intelligent automation across the RFQ lifecycle. AWS Lambda and Amazon API Gateway powered event-driven workflows that processed incoming RFQs, triggered document ingestion pipelines, and orchestrated proposal generation without infrastructure management overhead. Amazon S3, DynamoDB, and Aurora supported structured and unstructured data storage, ensuring durability, low latency, and seamless access to historical procurement intelligence.
AWS also enabled advanced AI, security, and observability capabilities across the platform. Amazon Bedrock and AgentCore powered agentic reasoning and generative AI workflows for compliance checks and proposal drafting, while Amazon OpenSearch Service enabled semantic retrieval for grounding responses in enterprise knowledge. AWS CloudWatch, AWS CloudTrail, and VPC-based isolation ensured real-time monitoring, full auditability, and secure communication across all services.
Tech Stack
The platform combined a modern full-stack architecture with AI-native backend services. The frontend and workflow interfaces supported RFQ intake, review, and collaboration, while backend services were powered by serverless compute and event-driven processing for scalable automation of document ingestion and proposal generation workflows.
The AWS cloud stack included Amazon API Gateway, AWS Lambda, Amazon Bedrock, Amazon Bedrock AgentCore, Amazon OpenSearch Service, Amazon Aurora, Amazon S3, Amazon DynamoDB, Amazon VPC, AWS CloudWatch, AWS CloudTrail, and AWS Backup, providing a fully managed, secure, and intelligent foundation.
DevOps and automation were driven through infrastructure-as-code and CI/CD practices, ensuring consistent deployments, environment reliability, and continuous delivery of model and workflow improvements.