Scatter Lab vs Cogent Labs

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Scatter Lab employs 1-50 people, while Cogent Labs has 100-500 employees.

Cogent Labs has raised more in total funding at $50M, compared to Scatter Lab's $15M — a gap of $35M. Combined, the two companies have completed 7 known funding rounds.

Cogent Labs leads with an Awaira Score of 55/100, while Scatter Lab sits at 38/100. That 17-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Scatter Lab was founded by Kim Jong-yoon in 2014. Cogent Labs was founded by Andrew Hall in 2016. Visit each company's profile on Awaira for a full founder biography.

Scatter Lab: Scatter Lab develops emotional AI and conversational applications in Korean, most notably Luda, a social chatbot designed for conversational companionship that engages users in casual, emotionally warm dialogue. The Seoul company applies social dialogue modelling to create AI characters that Korean users interact with for emotional support and social connection, a use case that has attracted significant user adoption particularly among younger Koreans.\n\nThe company raised approximately $15 million in venture funding from Korean investors including Kakao Ventures and DSC Investment. Scatter Lab has experienced regulatory and public controversy following the launch of its original Luda chatbot in 2021, which was suspended after concerns about data privacy practices and the chatbot production of offensive content, prominent to a significant redesign and relaunch with improved safety controls. The company has continued to develop its emotional AI technology while navigating the governance challenges of deploying social chatbots at consumer scale.\n\nScatter Lab operates in the social AI and AI companionship market alongside Character.ai, Replika, and Nomi.ai, serving a use case where emotional resonance and conversational naturalness are the primary product quality metrics rather than factual accuracy or task completion. The Korean market context, including social pressures and loneliness among young adults, creates specific demand for AI companionship products that is driving user growth despite regulatory attention. The company challenges with its first Luda release have informed approaches to responsible deployment that the broader AI companionship market is still developing. 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.

Scatter Lab 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.

Scatter Lab has about 1-50 employees; Cogent Labs has about 100-500. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

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