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Invisible Technologies Tech Stack
AI data prep and labeling platform for enterprise models
Invisible Technologies operates a data-preparation and model-tuning platform that cleans, labels, and structures company data for AI systems. The stack reflects a hybrid infrastructure approach: Python + SQL for data pipelines (Kafka, Delta Lake, Unity Catalog), LLM integrations (OpenAI, Cohere, Hugging Face, LangChain), and cloud deployment (GCP, AWS, Kubernetes). With engineering-heavy hiring (13 of 20 active roles) weighted toward senior and principal engineers, the company is scaling infrastructure and client-facing deployment capabilities while addressing internal data governance and pipeline-metric challenges.
Tech Stack 28 technologies
Core StackPython Hugging Face LangChain OpenAI Pinecone Docker FastAPI Kubernetes AWS Kafka Unity Catalog Delta Lake Salesforce GitLab TypeScript JavaScript React Metabase Excel Google Workspace SQL GCP LinkedIn Cohere HTML CSS Google Sheets Google Apps Script
What Invisible Technologies Is Building
◆Challenges
- Operational challenges
- Scaling models
- Improving platform performance
- Messy ambiguous workflows
- Process design improvement
- Data hygiene issues
- Data governance challenges
- Pipeline metrics improvement
- Client-facing deployments
- Client success
▲Active Projects
- Ai-driven solutions
- Client-facing deployments
- Next-generation marketplace launch
- Ai learning events
- Scalable operational processes from 0-1
- Event-based campaigns
- Linkedin email campaigns
- Lead capture workflows
- Shared infrastructure components
- Roadshows
Hiring Activity
Steady20 roles · 8 in 30d
Department
Seniority
Company intelligence
