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 $70.2M, compared to Eigen Technologies's $37M — a gap of $33.2M. Combined, the two companies have completed 7 known funding rounds.

Rasa leads with an Awaira Score of 60/100, while Eigen Technologies sits at 58/100. That 2-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

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 got there first, launching in 2014 — that's 2 years of extra runway. Rasa didn't arrive until 2016. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Both Rasa and Eigen Technologies report about 100-500 employees. Team size is a rough proxy for scale, but lean AI companies routinely punch above their headcount.

Yes — they're direct rivals. Both Rasa and Eigen Technologies compete in NLP, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.