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Cogent Labs vs Rasa

Side-by-side on valuation, funding, investors, founders & more

Comparison updated: April 2026

Two NLP companies going head to head.

Head-to-Head Verdict

Rasa leads on 2 of 4 metrics

Cogent Labs

0 wins

-Funding
-Awaira Score
=Team Size
=Experience

Rasa

2 wins

+Funding
+Awaira Score
=Team Size
=Experience

Key Numbers

Valuation
N/A
N/A
Total Funding
$50M
$70.2M
Awaira Score
55/100
60/100
Employees
100-500
100-500
Founded
2016
2016
Stage
Series C
Series C
Cogent LabsRasa
Cogent Labs logo
Cogent Labs

🇯🇵 Japan · Andrew Hall

Series CNLPEst. 2016

Valuation

N/A

Total Funding

$50M

Awaira Score55/100

100-500 employees

Full Cogent Labs Profile →
Winner
Rasa logo
Rasa

🇺🇸 United States · Alan Nichol

Series CNLPEst. 2016

Valuation

N/A

Total Funding

$70.2M

Awaira Score60/100

100-500 employees

Full Rasa Profile →
Market Context

Both companies compete in the NLP space, though from different geographies — Cogent Labs in Japan and Rasa in United States. Both are at the Series C stage, meaning they face similar scaling challenges and investor expectations.

🔬

Analyst Summary

Built from real data · Updated April 2026

Companies

In the NLP market, Cogent Labs and Rasa represent two distinct approaches. 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. 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.

Funding & Valuation

Neither company has publicly disclosed a valuation. Cogent Labs has raised $50M while Rasa has raised $70.2M, keeping their war chests in the same ballpark.

Growth Stage

Both companies were founded in 2016, giving them equivalent market tenure. Both sit at the Series C stage, suggesting similar risk profiles for potential investors. Team sizes also differ: Cogent Labs employs 100-500 people versus Rasa's 100-500.

Geography & Outlook

Geography separates them: Cogent Labs in 🇯🇵 Japan and Rasa in 🇺🇸 United States, each benefiting from local ecosystems. On Awaira's 0-100 scale, the gap is minimal — Cogent Labs scores 55 and Rasa scores 60. Under Andrew Hall and Alan Nichol respectively, both companies continue to chart aggressive growth paths.

Funding Velocity

Cogent Labs

Total Rounds4
Avg. Round Size$12.5M
Funding Span4 yrs

Rasa

Total Rounds4
Avg. Round Size$17.6M
Funding Span4 yrs

Funding History

Cogent Labs has completed 4 funding rounds, while Rasa has gone through 4. Cogent Labs's most recent round was a Series C of $27.5M, compared to Rasa's Series C ($38.6M). Both are currently at the Series C stage.

Team & Scale

Team sizes are in the same ballpark: Cogent Labs has about 100-500 people and Rasa has around 100-500. Both companies were founded in 2016. Geographically, they're in different markets — Cogent Labs operates out of Japan and Rasa from United States.

Metrics Comparison

MetricCogent LabsRasa
💰Valuation
N/A
N/A
📈Total Funding
$50M
$70.2MWINS
📅Founded
2016
2016
🚀Stage
Series C
Series C
👥Employees
100-500
100-500
🌍Country
Japan
United States
🏷️Category
NLP
NLP
Awaira Score
55
60WINS

Key Differences

📈

Funding gap: Rasa has raised $20.2M more ($70.2M vs $50M)

🌍

Market base: 🇯🇵 Cogent Labs (Japan) vs 🇺🇸 Rasa (United States)

⚔️

Direct competitors: Both operate in the NLP market segment

Awaira Score: Rasa scores 60/100 vs Cogent Labs's 55/100

Which Should You Choose?

Use these signals to make the right call

Cogent Labs logo

Choose Cogent Labs if…

  • Japan-based for regional compliance or proximity
  • 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
Rasa logo

Choose Rasa if…

Top Pick
  • Higher Awaira Score — 60/100 vs 55/100
  • Stronger investor backing — raised $70.2M
  • United States-based for regional compliance or proximity
  • 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

Funding History

Cogent Labs raised $50M across 4 rounds. Rasa raised $70.2M across 4 rounds.

Cogent Labs

Series C

Jun 2020

$27.5M

Series B

Feb 2019

$14M

Series A

Oct 2017

$6M

Seed

Jun 2016

$2.5M

Rasa

Series C

Jun 2020

$38.6M

Series B

Feb 2019

$19.7M

Series A

Oct 2017

$8.4M

Seed

Jun 2016

$3.5M

Users Also Compare

FAQ — Cogent Labs vs Rasa

Is Cogent Labs bigger than Rasa?
Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Cogent Labs employs 100-500 people, while Rasa has 100-500 employees.
Which company raised more funding — Cogent Labs or Rasa?
Rasa has raised more in total funding at $70.2M, compared to Cogent Labs's $50M — a gap of $20.2M. Combined, the two companies have completed 8 known funding rounds.
Which company has a higher Awaira Score?
Rasa leads with an Awaira Score of 60/100, while Cogent Labs sits at 55/100. That 5-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.
Who founded Cogent Labs vs Rasa?
Cogent Labs was founded by Andrew Hall in 2016. Rasa was founded by Alan Nichol in 2016. Visit each company's profile on Awaira for a full founder biography.
What does Cogent Labs do vs Rasa?
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. 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.
Which company was founded first?
Both Cogent Labs and Rasa launched in 2016. Same year, but even a few months' head start matters in AI — early movers lock in data, talent, and customer relationships fast.
Which company has more employees?
Both Cogent Labs and Rasa report about 100-500 employees. Team size is a rough proxy for scale, but lean AI companies routinely punch above their headcount.
Are Cogent Labs and Rasa competitors?
Yes — they're direct rivals. Both Cogent Labs and Rasa compete in NLP, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.

Bottom Line

It's close. Both Cogent Labs and Rasa are strong players, and picking a winner depends on what you're looking for. Check each profile for the full picture.

Who Should You Watch?

This one's genuinely too close to call. Both companies are competitive, and the winner will likely come down to execution over the next 12-18 months. Follow both profiles on Awaira to track funding rounds, team changes, and score updates.

Deep Dive