Rasa vs Eigen Technologies

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Rasa employs 100-500 people, while Eigen Technologies has 100-500 employees.

Rasa has raised more in total funding at $75M, compared to Eigen Technologies's $37M — a gap of $38M.

Rasa holds the higher Awaira Score at 60/100, compared to Eigen Technologies's 58/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 2-point gap that reflects meaningful differences in scale or traction.

Rasa was founded by Alan Nichol in 2016. Eigen Technologies was founded by Lewis Liu in 2014. Visit each company's profile on Awaira for a full founder biography.

Rasa: Rasa builds an open-source conversational AI framework and an enterprise-grade dialogue management platform used by developers and large organizations to deploy contextual AI assistants. The core open-source product has accumulated millions of downloads and serves as the foundation for production chatbots and voice assistants across industries including banking, telecom, and healthcare.\n\nThe company raised approximately 75 million USD through Series C and has enterprise customers in regulated industries that require on-premise or private cloud deployment rather than SaaS-based NLP services. Rasa competes directly with managed platforms from Dialogflow, Amazon Lex, and IBM Watson by offering full data control and model customization unavailable on those services.\n\nAs enterprises grow more cautious about sending customer conversation data to third-party cloud providers, the demand for self-hosted conversational AI infrastructure strengthens Rasa position. The platform is particularly well-suited for organizations in the EU and financial sectors operating under strict data residency requirements, giving Rasa a structural moat that pure-SaaS NLP competitors cannot easily replicate. Eigen Technologies: Eigen Technologies builds natural language processing software for document-intensive workflows in financial services, legal, and insurance. The platform uses machine learning models to extract structured data from unstructured contracts, prospectuses, loan documentation, and regulatory filings, enabling financial institutions to automate manual review processes that previously required large teams of analysts.\n\nThe company raised approximately $37 million including a $17 million Series B round led by Goldman Sachs and Lakestar. Its client base includes major investment banks, asset managers, and insurance groups that use the platform to accelerate due diligence, contract management, and regulatory reporting workflows. Eigen reports that clients achieve extraction accuracy rates that match or exceed human reviewers on structured financial documents.\n\nEigen competes in the intelligent document processing market alongside Kofax, ABBYY, and newer AI-native entrants including Zuva and Luminance. Its focus on financial services document types and its ability to train accurate models from small labelled datasets differentiate it in an enterprise sales process where production-grade accuracy on specialist document types is the primary evaluation criterion. The company is headquartered in London with offices in New York, serving both UK and US financial institutions.

Eigen Technologies was founded first in 2014, giving it 2 years of additional market experience. Rasa was founded later in 2016. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Both Rasa and Eigen Technologies report similar employee counts of approximately 100-500. Team size is often a proxy for operational scale, though lean AI companies can punch well above their headcount.

Yes, Rasa and Eigen Technologies are direct competitors — both operate in the NLP space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.