Conversational AI solutions for digital marketers, brand managers, and multi-location enterprises


Opcodera is a software product company building developer-led, cloud-native solutions for digital marketing, link management, and customer engagement. Its flagship product, EQRGen, is a leading QR code generation and URL shortening platform designed to empower digital marketers, brand managers, and enterprise customers with dynamic, branded short links and trackable QR codes. EQRGen streamlines campaign creation, audience engagement, and multi-channel attribution workflows while ensuring high-performance link delivery and real-time scan analytics across global markets.
MarTech & Digital Advertising (Marketing Technology)
Amazon Bedrock, Bedrock AgentCore Runtime, AgentCore Memory, AgentCore Identity, AgentCore Gateway, AgentCore Policy (Cedar), Bedrock Guardrails, Bedrock Knowledge Bases, AWS Lambda, Amazon ECS, AWS Fargate, Amazon API Gateway, Amazon S3, Amazon RDS for PostgreSQL, Amazon OpenSearch Service, Amazon CloudFront, AWS Secrets Manager, AWS KMS, AWS IAM, Amazon Cognito, Amazon CloudWatch, AWS X-Ray
Opcodera required a robust, intelligent, and conversation-first platform to support EQRGen’s rapidly expanding base of enterprise marketers running high-volume QR and short-link campaigns. The system needed to seamlessly handle multi-turn natural language interactions, particularly during peak campaign launches when marketers configure hundreds of dynamic QR codes simultaneously across regions, ensuring sub-second agent response times and zero session loss. Achieving high availability and persistent conversational context across long-running marketing workflows was a critical requirement, necessitating an agent runtime that could scale dynamically without burdening Opcodera’s engineering team with infrastructure management.
Data-driven precision and operational agility were key priorities to maintain a competitive edge in the crowded QR and link-management space. EQRGen required a sophisticated mechanism to interpret marketer intent across vague and complex requests (such as “create 100 QR codes for our festive store launches and tell me which ones underperform”), necessitating advanced multi-step reasoning, tool orchestration, and Retrieval-Augmented Generation grounded in EQRGen’s product documentation. Additionally, automation was critical to eliminate dashboard navigation overhead, reduce time-to-insight, and enable self-serve campaign optimization without human support intervention.
To balance cost and performance, Opcodera needed an architecture that scaled agent compute on demand while protecting margins on EQRGen’s free-tier and entry-level paid customers. The architecture required intelligent guardrails to manage feature gating across plan tiers and prevent misuse, while significantly reducing customer acquisition cost (CAC) and support overhead. Furthermore, the solution demanded a secure and isolated environment for processing customer campaign data, brand assets, and analytics, ensuring a compliant foundation for enterprise expansion across regulated industries.

Dashboard Friction and User Activation Drop-Off: EQRGen’s traditional click-driven dashboard created significant onboarding friction for non-technical marketers. New users frequently abandoned the platform before completing their first dynamic QR campaign, and enterprise teams struggled to operationalize bulk campaign workflows without dedicating engineering resources. Opcodera needed a conversational interface that could collapse multi-step workflows into single natural-language requests.
Multi-Step Reasoning and Tool Orchestration Complexity: Building an agent that could reliably translate marketer intent into correct sequences of API calls (generate QR, apply branding, configure expiry, fetch analytics, segment by geography) required moving beyond simple chatbot architectures. The challenge was orchestrating long-horizon, multi-tool workflows while preserving conversational context across sessions and preventing tool-call errors that would erode user trust.
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Opcodera implemented Amazon Bedrock as the reasoning core of EQRGen’s new conversational layer, with Anthropic Claude handling natural language understanding, multi-step planning, and response generation.
AgentCore Memory was deployed to retain each user’s brand kit (colors, logo, default short domain), naming conventions, and recent campaign history, eliminating repetitive context-setting and accelerating every subsequent interaction.
AgentCore Gateway exposes EQRGen’s existing internal APIs (QR generation, link shortening, analytics, batch operations, user management) as MCP-compatible tools, allowing the agent to invoke them safely and reliably.
A Cedar-based AgentCore Policy framework was implemented to enforce plan-tier entitlements at the agent layer, automatically blocking premium tool calls for free-tier users and surfacing contextual upgrade prompts instead of generic errors.
Bedrock Knowledge Bases were integrated with EQRGen’s product documentation, help articles, and best-practice guides, allowing the agent to answer in-product questions (“what’s the difference between static and dynamic QR codes?”, “how should I name campaigns for tracking?”) with grounded, accurate responses rather than hallucinated text.
AWS Secrets Manager and AWS KMS handle the encryption and rotation of API keys, brand credentials, and customer-managed integrations. Amazon Cognito provides user authentication and session management, while VPC endpoints ensure that all agent traffic between Bedrock, Lambda, and EQRGen’s data plane remains private. This architecture provides the foundation for SOC 2 compliance and enterprise-grade data handling required by Opcodera’s regulated-industry customers.
Amazon CloudWatch and AWS X-Ray provide end-to-end visibility into agent reasoning chains, tool-call latency, and customer interaction patterns. This observability layer enables Opcodera’s product team to identify failed tool calls, optimize prompt strategies, and continuously refine guardrails based on real usage telemetry, ensuring EQRGen improves with every release cycle.
The AWS solution delivered transformative improvements across EQRGen’s key product, commercial, and operational metrics:


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