Overall Winner: Casetext·75/ 100
C
CasetextWinner
VS

Casetext vs Everlaw

In-depth comparison — valuation, funding, investors, founders & more

Winner
C
Casetext

🇺🇸 United States · Jake Heller

AcquiredAI LegalEst. 2013

Valuation

$650M

Total Funding

$64M

75
Awaira Score75/100

120 employees

Full Casetext Profile →
E
Everlaw

🇺🇸 United States · AJ Shankar

Series DAI LegalEst. 2010

Valuation

$2B

Total Funding

$517M

71
Awaira Score71/100

525 employees

Full Everlaw Profile →
🔬

Analyst Summary

Generated from real data · No AI hallucinations

Both Casetext and Everlaw compete directly in the AI Legal space, making this a head-to-head matchup within the same market segment. Casetext is an AI-powered legal research and document automation platform founded in 2013. Everlaw is an AI-powered legal technology platform founded in 2010 that specializes in e-discovery, document review, and litigation support.

Everlaw carries a valuation of $2B, which is 3.1x higher than Casetext's $650M. On the funding side, Everlaw has raised $517M in total — $453M more than Casetext's $64M.

Everlaw has 3 years more market experience, having been founded in 2010 compared to Casetext's 2013 founding. In terms of growth stage, Casetext is at Acquired while Everlaw is at Series D — a meaningful difference for investors evaluating risk and upside.

Both companies are headquartered in 🇺🇸 United States, competing for the same regional talent and customer base. On Awaira's 0–100 composite score, both companies are closely matched — Casetext scores 75 and Everlaw scores 71.

Metrics Comparison

MetricCasetextEverlaw
💰Valuation
$650M
$2BWINS
📈Total Funding
$64M
$517MWINS
📅Founded
2013WINS
2010
🚀Stage
Acquired
Series D
👥Employees
120
525
🌍Country
United States
United States
🏷️Category
AI Legal
AI Legal
Awaira Score
75WINS
71

Key Differences

💰

Valuation gap: Everlaw is valued 3.1x higher ($2B vs $650M)

📈

Funding gap: Everlaw has raised $453M more ($517M vs $64M)

📅

Market experience: Everlaw has 3 years more (founded 2010 vs 2013)

🚀

Growth stage: Casetext is at Acquired vs Everlaw at Series D

👥

Team size: Casetext has 120 employees vs Everlaw's 525

⚔️

Direct competitors: Both operate in the AI Legal market segment

Awaira Score: Casetext scores 75/100 vs Everlaw's 71/100

Which Should You Choose?

Use these signals to make the right call

C

Choose Casetext if…

Top Pick
  • Higher Awaira Score — 75/100 vs 71/100
  • Casetext is an AI-powered legal research and document automation platform founded in 2013
E

Choose Everlaw if…

  • More established by valuation ($2B)
  • Stronger investor backing — raised $517M
  • More market experience — founded in 2010
  • Everlaw is an AI-powered legal technology platform founded in 2010 that specializes in e-discovery, document review, and litigation support

Funding History

Casetext raised $64M across 3 rounds. Everlaw raised $517M across 3 rounds.

Casetext

Series C

Jun 2021

Lead: Menlo Ventures

$36M

Series B

Sep 2018

$13M

Series A

Jan 2017

Lead: Greycroft Partners

$15M

Everlaw

Series C

Jan 2018

Series B

Jan 2014

Series A

Jan 2012

Investor Comparison

No shared investors detected between these two companies.

Unique to Casetext

Menlo VenturesGreycroft Partners

Users Also Compare

FAQ — Casetext vs Everlaw

Is Casetext bigger than Everlaw?
By valuation, Everlaw is the larger company at $2B versus $650M — a 3.1x difference. Size can also be measured by team: Casetext employs 120 people while Everlaw has 525 employees.
Which company raised more funding — Casetext or Everlaw?
Everlaw has raised more in total funding at $517M, compared to Casetext's $64M — a gap of $453M. Combined, the two companies have completed 6 known funding rounds.
Which company has a higher Awaira Score?
Casetext holds the higher Awaira Score at 75/100, compared to Everlaw's 71/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 4-point gap that reflects meaningful differences in scale or traction.
Who founded Casetext vs Everlaw?
Casetext was founded by Jake Heller in 2013. Everlaw was founded by AJ Shankar in 2010. Visit each company's profile on Awaira for a full founder biography.
What does Casetext do vs Everlaw?
Casetext: Casetext is an AI-powered legal research and document automation platform founded in 2013. The company develops software that assists legal professionals with legal research, contract analysis, and document drafting through machine learning and natural language processing technologies. Its flagship product, CoCounsel, is an AI legal assistant that helps attorneys perform legal research, due diligence, and document review more efficiently. The platform integrates generative AI capabilities to analyze case law, statutes, and legal documents, enabling lawyers to reduce time spent on routine tasks and focus on higher-value work. Casetext positions itself in the legal AI market alongside competitors like LexisNexis, Westlaw, and newer entrants focused on AI-assisted legal work. The company has built its technology on proprietary legal databases and machine learning models trained on legal content. Its customer base includes law firms, in-house legal departments, and corporate legal teams seeking to modernize their research and document workflows. Founded with $64M in total funding, Casetext achieved a $700M valuation before being acquired, demonstrating significant growth in the legal technology sector. The acquisition reflects the increasing consolidation in legal AI as larger players and investors recognize the market opportunity. The company represents broader trends toward AI adoption in professional services, particularly in knowledge-intensive industries like law. Casetext pioneered accessible AI-assisted legal research for attorneys by combining generative AI with specialized legal training data. Everlaw: Everlaw is an AI-powered legal technology platform founded in 2010 that specializes in e-discovery, document review, and litigation support. The company provides software solutions that leverage artificial intelligence and machine learning to help legal teams manage large volumes of documents, identify relevant evidence, and streamline the discovery process in litigation and investigations. Everlaw's platform enables lawyers to conduct predictive coding, automated categorization, and advanced search across complex document repositories, reducing time and costs associated with traditional manual review. The company serves law firms, corporate legal departments, and government agencies handling complex litigation matters. Everlaw has achieved a $2.0 billion valuation following $517 million in total funding through Series D stage, positioning it as a significant player in the legal AI sector. The platform competes with established e-discovery providers and emerging legal tech companies offering AI-driven document analysis. Everlaw's growth trajectory reflects increasing demand for AI solutions in legal services, particularly as litigation volumes grow and cost pressures mount on legal departments. The company's focus on accessibility and user experience has contributed to its market traction among both large enterprises and mid-market legal organizations. Its continued funding rounds support product development and market expansion. Everlaw combines enterprise-grade e-discovery capabilities with accessible AI-driven document intelligence for diverse legal market segments.
Which company was founded first?
Everlaw was founded first in 2010, giving it 3 years of additional market experience. Casetext was founded later in 2013. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.
Which company has more employees?
Casetext has approximately 120 employees, while Everlaw has approximately 525. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.
Are Casetext and Everlaw competitors?
Yes, Casetext and Everlaw are direct competitors — both operate in the AI Legal space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.