Cogent Labs vs Eigen Technologies

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

Cogent Labs has raised more in total funding at $50M, compared to Eigen Technologies's $37M — a gap of $13M. Combined, the two companies have completed 7 known funding rounds.

Eigen Technologies leads with an Awaira Score of 58/100, while Cogent Labs sits at 55/100. That 3-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Cogent Labs was founded by Andrew Hall in 2016. Eigen Technologies was founded by Lewis Liu in 2014. Visit each company's profile on Awaira for a full founder biography.

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. 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. Cogent Labs 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 Cogent Labs 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 Cogent Labs and Eigen Technologies compete in NLP, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.