AI/ML
Data/Analytics
Enterprise SaaS

Hex Technologies

AI analytics and collaborative data platform

CORE INFO

$271.5M
Total Funding
Series D+
Round
2019
Founded
San Francisco, CA
Headquarters

Hex Technologies sells subscription software to data teams and business users at organizations that need to explore company data, build analyses and dashboards, and share trusted answers. Its platform brings together code-based and no-code workflows with governed AI-assisted analytics.

  • Latest financing: $100 million announced October 27, 2026, at a reported $1.2 billion valuation, with Peak XV Partners identified as the lead investor.axios.comforbes.com
  • Paying customers: TechCrunch reported 450 in March 2023, alongside 10× user-base growth over the prior year.techcrunch.com
  • Forbes reported that Hex deleted millions of lines of older product code after its best-ever quarter in Q1 2026, as the company pursued an agent-first product direction.forbes.com

WHY WE WOULD WORK AT HEX TECHNOLOGIES

Make Everyone Data-Savvy

Help advance Hex's mission to "make everyone a data person" by making trusted analytics accessible across technical and business teams.

Build Agentic Analytics

Work on an AI analytics platform combining natural-language questions, SQL, Python, R, no-code exploration, semantic context, and governed AI agents.

Shape Collaborative Work

Join a builder-focused team that values quality, craft, speed, few meetings, and direct feedback while connecting analysts, data scientists, and business users.

Grow With Real Momentum

Help scale a platform used by more than 2,000 organizations, including Reddit, Figma, Notion, HubSpot, and Anthropic, as Hex expands its agent-first strategy.

Create Customer Impact

Build tools behind outcomes such as 92% faster ticket resolution at Supabase, 97% less QBR preparation at EliseAI, and 4–8× faster workflows at Whatnot.

Solve Trust at Scale

Tackle one of AI's hardest problems: making answers reliable through governance, lineage, permissions, semantic models, auditability, and integrations with Snowflake, Databricks, and dbt.

MARKET AND TRACTION

GROWTH TACTICS

  • Hex expands adoption by combining natural-language analytics, SQL, Python, R, no-code exploration, collaborative notebooks, dashboards, data apps, semantic context, governance, and AI agents in one platform.

  • The company targets both technical data teams and business users through free, Team, and Enterprise SaaS offerings, while integrating with warehouses, databases, semantic layers, metadata systems, Slack, Claude, and ChatGPT-compatible tools.
  • NOTABLE CUSTOMERS

  • Publicly listed customers include Reddit, Notion, HubSpot, Figma, Ramp, Chime, LangChain, Supabase, Modal, Calendly, ClickUp, Doximity, Whatnot, Snowflake, and Databricks.

  • Hex serves organizations across technology, financial services, healthcare, life sciences, retail, media, professional services, energy, manufacturing, and AI.
  • KEY METRICS

    ✦ KEY METRIC
  • Hex has raised approximately $271.5M in publicly disclosed funding, including a $100M financing round announced in October 2026 at a reported $1.2B valuation.

  • Public traction disclosures include 450 paying customers in March 2023, more than 1,500 teams in 2025, and more than 2,000 customers on the company's About page; a 2026 company announcement reported more than 2,500 customers globally.

  • TechCrunch reported 10× user-base growth and 4× revenue growth in the year before March 2023.
  • COMPETITIVE ADVANTAGE

  • Hex differentiates by connecting fragmented BI, notebook, spreadsheet, SQL, and AI-assistant workflows in a governed collaborative workspace.

  • Its platform combines code, no-code, and natural language while grounding answers in organizational context, semantic models, permissions, lineage, and auditability.
  • PRODUCT AND TECH

    AI Analytics Platform

    Hex provides natural-language analytics and AI agents that answer questions using organizational data, business definitions, permissions, and context. Users can generate and inspect SQL and Python analyses while maintaining traceability and governance.

    Collaborative Data Notebooks

    Its cloud-based notebooks combine SQL, Python, R, visualizations, dataframes, and no-code cells in a shared workspace. This supports collaborative analytics, data science, and reproducible workflows.

    Dashboards And Data Apps

    Users can turn analyses into interactive dashboards, reports, embedded analytics experiences, and internal or customer-facing data applications. Features include row-level security, white-labeling, and REST APIs.

    Semantic Governance Layer

    Hex connects dbt code and semantic models, Snowflake semantic views, warehouse metadata, documentation, and other organizational context. Governance capabilities include permissions, lineage, audit logging, observability APIs, and controls for more trusted answers.

    Warehouse Integrations

    The platform connects with Snowflake, BigQuery, Databricks, Amazon Redshift, PostgreSQL, ClickHouse, dbt, Airflow, Dagster, Slack, Claude, and ChatGPT-compatible tools. Its Snowflake integration supports in-database SQL and Python/Snowpark execution, alongside private-cloud, single-tenant, and Snowflake-native deployment options.

    COMPANY CULTURE

    Values

  • Accelerate human insight

  • Make everyone a data person

  • Build beautiful, useful products

  • Help people do great things with data together
  • Operating Principles

  • Prioritize quality and craft

  • Move with speed and bias toward action

  • Favor trusted, governed, and reproducible data work

  • Combine code, no-code, and natural language workflows
  • Work Style

  • Operate as a team of builders and data enthusiasts

  • Keep barriers low for nontechnical users while supporting technical depth

  • Emphasize collaboration over isolated analysis

  • Maintain a relatively low-meeting environment
  • Team Cadence

  • Use feedback and support to help colleagues succeed

  • Work across AI, notebooks, data apps, infrastructure, design, support, partnerships, and sales

  • Connect data teams and business users through shared workflows
  • Learning & Growth

  • Work on evolving AI analytics and agent-oriented products

  • Learn across SQL, Python, R, no-code analytics, and semantic data workflows

  • Develop expertise in governance, context, and trusted AI-generated analysis