Customer Case Study: Houdiny AI – AI-Powered Lead Outreach Assistant with AWS Service Catalog Deployment

ACE Opportunity ID: O6822128

Houdiny is an intelligent sales and outreach saas platform designed to help businesses find, enrich, and engage potential leads automatically. The platform allows companies to scale their sales efforts without losing the personal touch.

The Houdiny system consists of three major modules:

• Lead Finder: A tool that discovers potential prospects based on their job role, location, and company data.
• Lead Enrichment: This module enhances each lead with deeper context. It uses AI to generate personalized outreach messages (one main message and two follow-ups) and provides a detailed analysis, including a “lead score” and the likelihood of engagement.
• Campaign Manager: A tool that automates the delivery, tracking, and optimization of campaigns across multiple communication channels.

2. Project Overview

Our engagement with Houdiny focused specifically on the application development of the Lead Enrichment module, as well as the complete Infrastructure Management of their AWS environment to ensure security and scalability.The primary objective of this engagement was to develop a comprehensive, AI-powered SaaS solution designed to automate and streamline the outreach process. To achieve this, we architected and deployed three components:

• Email Agent: This component generates personalized and targeted email outreach messages based on specific lead information. By automating the crafting of messages, businesses can ensure that every communication is contextually relevant and timely

• LinkedIn Agent: Similar to the email agent, the LinkedIn agent creates and sends messages tailored to potential leads on LinkedIn. This allows businesses to leverage this critical networking platform for more effective, professional engagement.
• Analysis Agent: This component performs in-depth analysis of lead data to help businesses uncover key insights. It categorizes leads based on engagement patterns and adds two actionable metrics—Engagement Likelihood and Intent Score—to guide more personalized and effective outreach strategies.

The solution combines the power of Generative AI to automate these critical business functions, improving outreach efficiency, reducing manual effort, and ensuring that every lead interaction is optimized for maximum impact.

3. Challenges

Houdiny AI aimed to build an enterprise-grade platform, but they encountered significant hurdles on two fronts: the operational inefficiencies their customers faced, and the technical limitations of their own internal infrastructure.

A. Operational & Business Challenges

Before implementing the message and lead-analysis components of the Houdiny solution, target customers faced significant barriers in their sales processes. Their traditional workflows were highly manual, time-consuming, and difficult to scale.

• Manual Outreach: Businesses spent considerable time manually crafting personalized emails for each lead. This process was inefficient, making it nearly impossible to scale outreach efforts as the business grew.
• Slow Response Times: Without automation, businesses struggled to engage leads promptly. This “response lag” often resulted in missed opportunities and reduced interest from potential clients.
• Fragmented Tools: Companies relied on a disjointed combination of tools for email campaigns, LinkedIn, and CRM. This fragmentation caused messaging inconsistencies and increased administrative overhead.
• Inefficient Data Analysis: Analyzing lead behavior involved manual reviews of spreadsheets, which was time-consuming and prone to human error. This limited the ability to gain real-time insights or adjust strategies quickly.
• Limited Personalization: Because manual customization is slow, many communications came across as generic. Businesses missed the opportunity to tailor content to individual lead preferences, resulting in lower engagement rates.

B. Infrastructure & DevOps Challenges

Internally, to solve these customer problems effectively, Houdiny AI needed to modernize their underlying cloud architecture. They faced several critical technical risks:

• Lack of Governance (Single Account Risk): Houdiny initially operated all workloads within a single AWS account. Staging and production environments were intermixed, creating a high risk of accidental outrages impacting live users.
• Security & Compliance: As the platform grew, strict adherence to data protection standards became mandatory. The existing setup lacked automated guardrails, proper network isolation, and the granular auditing required for a SaaS application handling sensitive data.
• Scalability Concerns: The infrastructure was not built to handle the “bursty” nature of the workload (e.g., a user uploading a file with 10,000 leads). The system struggled to scale compute resources instantly, leading to performance bottlenecks during peak usage.

4. Proposed Solution

To address these multi-faceted challenges, we designed and implemented a secure, scalable, and fully automated AWS environment. The solution merged advanced Generative AI capabilities with AWS best practices for governance.

A. Infrastructure & Governance Implementation

We partnered with Houdiny AI to transition from a fragile single-account setup to a mature, multi-account architecture. This ensured the platform was secure, compliant, and easy to manage.

• Landing Zone Implementation: We deployed an AWS Control Tower–based Landing Zone to establish a strategic multi-account environment. This strictly separated Management, Staging, and Production workloads, eliminating the risk of accidental outages affecting live users.
• Standardized Provisioning: We implemented AWS Service Catalog, enabling the development team to self-serve pre-configured, compliant infrastructure resources. This reduced administrative bottlenecks and ensured that every new environment met security standards automatically.
• Security & Compliance: We enforced a “Least Privilege” access model using AWS IAM Identity Center. To meet compliance requirements for handling lead data, we enabled AWS Config and AWS CloudTrail for continuous auditing and real-time monitoring of resource changes.

B. Application Implementation (Lead Enrichment Module)

On the application side, we designed and implemented the Lead Enrichment module to fully leverage Generative AI and high-performance computing, plus also integrating the solution with their frontend and backend.

• Generative AI Integration: We integrated llm apis to power the core enrichment engine. This allows the system to analyze unstructured lead data and generate highly personalized, context-aware emails and LinkedIn messages that sound authentically human.
• High-Performance Compute: We implemented AWS Batch to handle the heavy computational load of processing large lead lists. This allows the system to process massive CSV files in parallel, reducing the processing time for thousands of leads from hours to minutes.
• Event-Driven Serverless Architecture: We utilized Amazon API Gateway, AWS Lambda, and Amazon EventBridge to orchestrate the entire workflow. This serverless design ensures the application scales automatically to handle burst traffic and incurs near-zero costs when idle.
• Modern Data Management: We migrated the data layer to Amazon Aurora, a cloud-native database that provides high availability and automated backups, ensuring the security and integrity of user campaign data.

5. Outcomes and Metrics

The transformation of Houdiny AI’s infrastructure and the integration of Generative AI have yielded immediate, measurable results. By moving from a manual, single-account setup to an automated, multi-account AWS environment, Houdiny AI achieved significant improvements in both operational efficiency and business performance.

Quantitative Business Impact Metrics

The following table outlines the dramatic shift in performance and capabilities:

Strategic Benefits

Beyond the metrics, the solution delivered critical strategic benefits that enabled Houdiny AI to scale:

• Enterprise-Grade Security: The implementation of AWS Control Tower and IAM Identity Center moved the company from a “security risk” status to being fully compliant with enterprise data standards, opening the door to larger B2B clients.
• Scalability on Demand: With AWS Batch and Serverless compute, the platform now handles spikes in user traffic (e.g., uploading bulk leads at once) without crashing or requiring manual server provisioning.
• Enhanced Decision Making: The new Analysis Agent allows sales teams to prioritize high-value prospects rather than wasting time on cold leads, fundamentally changing how their users operate.

6. Conclusion

Houdiny AI has successfully transitioned from a manual, unscalable operation to a market-leading, AI-driven SaaS platform. By partnering with us to leverage generative AI combined with AWS infrastructure for intelligence and AWS Control Tower for governance, they have not only solved their immediate scalability challenges but have also built a foundation for long-term growth.

The solution demonstrates the power of AWS for SMBs: providing enterprise-level capabilities—like Generative AI and automated compliance—without the need for an enterprise-sized IT team.