Further is a 51–200 person consulting firm built around data strategy, cloud infrastructure, and AI platform delivery. The tech stack reveals a production-AI focus: RAG systems (Pinecone, Weaviate, LangChain, LlamaIndex), LLMOps workflows, and API-first architecture (FastAPI, gRPC) sitting on GCP and Snowflake. Hiring is heavily weighted toward data (20 roles) and engineering (15), with senior and director positions dominating — a staffing shape that reflects the high-touch, outcomes-focused services model and the complexity gap they're solving: their pain-point list surfaces "gap between prototypes and production" and "AI investments becoming shelf-ware," signaling that the core friction for their buyers isn't ideation but operationalization at scale.
Tech Stack 71 technologies
What Further Is Building
◆Challenges
- Ai strategy undefined across industries
- High availability security cost-effectiveness
- Gap between prototypes and production
- Accurate data
- Ai investments becoming shelf-ware
- Data accuracy issues
- Experiment backlog management
- Lack of actionable insights
- Profile-stitching or data-latency issues
- Ensuring compliant data usage
▲Active Projects
- Postgresql schema design
- Ai adoption roadmap
- Rag systems
- Deployment of web applications on google cloud platform
- Rag system design
- Llmops workflows for production ai models
- Client discovery and hypothesis backlog
- Cloud-based commercial ai products
- Ai model integration into production apis
- Web application development using svelte, go, and fastapi
Hiring Activity
Department
Seniority
Notable leadership hires: UX IA Lead, Product Director, Data Strategy Director, Chief of Staff
