AI platform for construction product discovery and project quoting
Parspec operates in the construction materials supply chain, where distributors and rep agencies still rely on spreadsheets and manual workflows to quote and bid projects. The tech stack reveals a company betting heavily on LLMs and agentic systems — vLLM, Ollama, LiteLLM, LangGraph, CrewAI, RAG — paired with careful observability (OpenTelemetry, Prometheus, Grafana) and ops tooling (Portkey, CodeRabbit). Active projects around document extraction, product specification understanding, and search ranking signal that their core challenge is turning messy, unstructured construction data into actionable intelligence at scale.
Parspec builds an AI-native platform to help construction distributors and rep agencies discover products, generate quotes, and manage projects faster. Founded in 2021 and based in the San Francisco Bay Area, the company serves over 300 MEP distributors and rep agencies by automating workflows that traditionally required manual data entry, spreadsheet wrangling, and phone calls. The platform combines product intelligence, AI-powered workflows, and ecosystem connectivity to address fragmentation across the $15 trillion construction supply chain. Hiring is concentrated in engineering and product, with a mix of senior and lead roles, signaling active platform development and scaling.
Parspec's stack includes vLLM, Ollama, LangGraph, and CrewAI for LLM operations, plus RAG, LoRA, and QLoRA for model fine-tuning. They use LiteLLM and Portkey for LLM orchestration and Prometheus/Grafana for observability.
Parspec helps construction distributors and rep agencies automate product discovery, quoting, and project management. Active projects center on agentic workflows, document extraction, product specification understanding, search ranking, and AI-powered operations.
Parspec'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.