FlowX.AI builds a production-grade multi-agent AI platform for banking and financial services, with 140+ pre-built agents and governance controls baked in. The tech stack reflects dual motives: a strong backend foundation (Java, .NET, Kubernetes, Kafka, gRPC) handles mission-critical workloads, while workflow orchestration tools (Camunda, Appian, Pega) and modern AI frameworks (LangChain, CrewAI, RAG, MCP) enable rapid agent assembly. Hiring velocity is accelerating across engineering and sales in parallel—a pattern that matches their stated pain points around scaling both production AI deployment and lead qualification in regulated verticals, suggesting they're moving from early customer wins into repeatability.
Tech Stack 34 technologies
Core StackJava .NET Kubernetes HubSpot Salesloft Playwright TypeScript Angular React JavaScript Python RAG LangChain Apache Kafka gRPC Docker AWS Apollo Outreach iOS Android Appian Camunda IBM Pega Semantic Kernel CrewAI MCP Spring Boot Azure+4 more
What FlowX.AI Is Building
◆Challenges
- Time cost expertise for ai agents
- Improving forecasting accuracy
- Accelerating digital product development
- Scalable ai deployment
- Building qualified pipeline
- Lead loss
- Scaling production ai platform
- Scaling inbound lead qualification
- Identifying qualified leads in regulated industries
- Scaling commercial operations
▲Active Projects
- Inbound traffic pattern analysis
- Inbound pipeline management
- Proof of concepts (pocs)
- Strategic growth in cee
- Scale gtm infrastructure
- Proof-of-concept development for ai agents
- Multi-channel demand gen campaigns
- Linkedin campaign management
- Growth of next-generation ai platform
- Lead qualification process
Hiring Activity
20 roles · 20 in 30d
Department
Seniority
Company intelligence
