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Prodigal Tech Stack

AI-powered loan servicing and collections platform for lenders and debt collectors

Software Development Mountain View, California 51–200 employees Founded 2018 Privately Held
prodigaltech.com LinkedIn

Prodigal builds AI agents for debt collection and loan servicing, trained on 400M+ consumer finance conversations. The tech stack reveals a machine-learning-first infrastructure: PySpark, MLflow, Databricks, dbt, and Apache Airflow power a data pipeline feeding voice AI models (ElevenLabs, Deepgram, WebRTC, Cartesia). The project list is heavily weighted toward voice AI agents and prompt engineering, while hiring is engineering-focused—7 of 13 open roles are engineering—and now adopting Terraform, signaling infrastructure scaling. Pain points cluster around real-time voice AI infrastructure and cloud cost optimization, both typical of LLM-heavy workloads.

Tech Stack 33 technologies

Core StackPySpark MLflow Python AWS Kubernetes Istio Prometheus Grafana Databricks Intercom Stripe Salesforce Zendesk MongoDB PostgreSQL AWS Lambda CloudFront Sentry CloudWatch dbt Apache Airflow Tableau Karpenter SAST ElevenLabs Cartesia Deepgram WebRTC Razorpay AWS SQS+2 more
AdoptingTerraform

What Prodigal Is Building

◆Challenges

  • Inefficiencies in lending and collections
  • Confusion in lending and collections
  • Improving collections and recoveries
  • Enhancing consumer experience
  • Scaling creative output
  • Reducing time to market for gtm assets
  • Driving soc2 compliance
  • Cloud cost optimisation
  • Real-time voice ai infrastructure
  • Reducing support response time

▲Active Projects

  • Voice ai agents
  • Ai agent development
  • Prompt engineering methodologies
  • High-priority ai projects
  • Llm reasoning
  • Ai agent deployment for loan servicing and collections
  • Design call flow diagrams for customer workflows
  • Process automation & internal tooling
  • Customer onboarding & implementation
  • Prompt engineering for voice ai

Hiring Activity

Accelerating15 roles · 5 in 30d

Department

Engineering
7
Design
1
Operations
1
Ops
1
Sales
1
Security
1
Support
1

Seniority

Mid
4
Lead
3
Senior
3
Intern
1
Junior
1
Manager
1
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About Prodigal

Prodigal operates in credit and collections, offering AI agents that interact with consumers to maximize payment recovery for lenders and debt collectors. Founded in 2018 and based in Mountain View, the company employs 51–200 people and is backed by Accel, Menlo Ventures, and Y Combinator. The platform combines interaction analytics, voice recognition, and generative AI to personalize outreach and improve recovery rates. The team spans engineering, design, sales, and security, with active hiring in the United States and India.

HeadquartersMountain View, California
Company Size51–200 employees
Founded2018
Hiring MarketsUnited States, India

Frequently Asked Questions

What technology powers Prodigal's voice AI agents?

Prodigal uses ElevenLabs, Deepgram, Cartesia, and WebRTC for voice; PySpark, MLflow, and Databricks for ML model training; and Apache Airflow for orchestration. The platform is deployed on AWS (Kubernetes, Lambda, CloudFront, SQS).

What is Prodigal currently building?

Voice AI agents for loan servicing and collections, prompt engineering methodologies for LLMs, AI agent deployment infrastructure, design of call flows, and process automation for internal tooling and customer onboarding.

How this profile is built

Prodigal's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.