Arkham offers an integrated Data & AI platform that unifies fragmented business data into a single source of truth. It enables metric standardization and the development of tailored machine learning and generative AI models to accelerate insights and automate operational processes.
Funding
$2.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Businesses struggle with fragmented data across disparate systems, hindering the ability to establish a unified view of operations. This fragmentation impedes accurate metric standardization and the effective application of advanced analytics and AI models. Consequently, organizations face challenges in accelerating insights, automating processes, and achieving operational efficiency.
Solution
Arkham provides an integrated Data & AI platform designed to unify fragmented data into a single source of truth. The platform facilitates the standardization of key business metrics and enables the development of tailored machine learning and generative AI models to address complex operational challenges. By consolidating data from various sources, Arkham empowers organizations to accelerate insight generation, automate critical business processes, and enhance overall operational efficiency. The platform offers a managed, UI-driven environment that streamlines the journey from raw data to production-ready assets, allowing teams to focus on value creation rather than infrastructure management.
Target Audience
Arkham targets technology and business teams within enterprises across various industries, including Infrastructure, Retail, CPG, Credit, Insurance, Manufacturing, and Private Equity, who need to unify data and leverage AI for operational improvement.
Features
- **Data Platform:** A managed, UI-driven environment for data unification, transformation, and governance.
- **Data Connectors:** A library of pre-built, production-grade integrations for automated data ingestion from diverse source systems.
- **Pipeline Builder:** A visual, canvas-based environment for orchestrating and transforming raw data into clean, production-grade assets with explicit data lineage.
- **Data Catalog:** A centralized, governed registry for discovering, understanding, and managing all data assets, ensuring versioning, auditability, and security.
- **Playground:** An integrated Trino SQL editor for interactive data exploration and validation of production-ready datasets.
- **AI Platform:** A suite of tools for building and deploying machine learning models and generative AI applications, including ML Hub for forecasting, anomaly detection, and segmentation, and TARS AI Copilot for AI-assisted development.
- **Ontology:** A framework for mapping datasets and models into structured business entities and actions to create a unified, consistent operational view.
- **Data Governance:** Features supporting data quality, lineage tracking, security, and compliance with standards such as SOC 2, GDPR, and ISO 27001.