Rasa vs Cogent Labs

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

Rasa has raised more in total funding at $75M, compared to Cogent Labs's $50M — a gap of $25M.

Rasa holds the higher Awaira Score at 60/100, compared to Cogent Labs's 55/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 5-point gap that reflects meaningful differences in scale or traction.

Rasa was founded by Alan Nichol in 2016. Cogent Labs was founded by Andrew Hall in 2016. 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. Cogent Labs: Cogent Labs develops AI document processing and text analysis software with specialised capabilities in Japanese character recognition, handwritten text, and structured document data extraction, targeting the Japanese financial services, insurance, and government sectors where large volumes of handwritten and mixed-format documents require processing with high accuracy in Japanese scripts including kanji, hiragana, and katakana. The Tokyo company applies deep learning models trained on large Japanese document datasets to achieve recognition accuracy on complex Japanese text that general OCR systems cannot match.\n\nThe company raised approximately $50 million in venture funding from investors including WiL and Goldman Sachs. Cogent Labs Tegaki handwriting recognition product has been deployed by major Japanese insurance companies, financial institutions, and public sector organisations to automate document digitisation workflows that previously required large manual data entry teams. The Japanese market for document AI is substantial given the volume of paper-based documents in government and financial services operations and the complexity of Japanese script that makes off-the-shelf OCR insufficient.\n\nCogent Labs competes in the Japanese document AI market against OBIC, NTT Data, and international intelligent document processing vendors including ABBYY and Kofax. Its Japanese-specific technical capabilities create a natural market advantage that English-first vendors struggle to match through localisation alone, as accurate Japanese handwriting recognition requires specialised model training that cannot be derived from models built primarily on Latin character datasets. The company has expanded internationally to address Korean and other East Asian scripts with similar character recognition complexity.

Both Rasa and Cogent Labs were founded in the same year — 2016. Despite sharing a founding year, they may have launched at different times within that year, which can matter in fast-moving AI markets.

Both Rasa and Cogent Labs 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 Cogent Labs 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.