Clients expect you to recommend the best AI tools, but you can't properly evaluate them without access to the data vendors require for testing. You're forced to rely on vendor demos and marketing claims rather than hands-on experience, undermining your role as the trusted technology advisor for your firm and clients.
Your firm needs to train attorneys and staff on new technologies, standardize best practices, and optimize workflows before deploying them on live matters, but you can't use client data for training. New associates need hands-on experience with document review platforms, eDiscovery tools, and contract analysis systems, yet providing that experience without exposing confidential information or risking conflicts is nearly impossible. Workflow optimization requires testing on realistic datasets to identify bottlenecks, but using actual client files for process improvement creates unacceptable risk.
Your firm needs to build internal tools, workflows, and AI capabilities that serve your clients' unique needs, but development requires data you don't have. Building custom document automation, matter management systems, or AI-assisted research tools demands realistic legal data for testing and validation. You can't use client files for development environments, the Enron data is a non-starter, and generic placeholder data fails to capture the complexity your tools must handle. You need specialized data that will enable the capabilities that set your firm apart.
Our patent-pending process generates relevant communications and documents (emails, meeting transcripts, contracts, regulatory filings) with embedded scenarios to evaluate legal AI tools, train staff, and demonstrate capabilities across litigation, investigations, and transactional work.
Seedless was co-founded by a seasoned attorney with extensive law firm experience managing complex eDiscovery projects, litigation technology, and client relationships at scale. The founding team combines deep understanding of law firm operations with technical expertise in AI/ML and unstructured data management to address the data challenges firms face when evaluating and implementing AI tools for discovery, document review, and client service.
Clients expect you to recommend the best AI tools, but you can't properly evaluate them without access to the data vendors require for testing. You're forced to rely on vendor demos and marketing claims rather than hands-on experience, undermining your role as the trusted technology advisor for your firm and clients.
Our datasets deliver measurable impact on your evaluation process and technology decisions:
Your firm needs to train attorneys and staff on new technologies, standardize best practices, and optimize workflows before deploying them on live matters, but you can't use client data for training. New associates need hands-on experience with document review platforms, eDiscovery tools, and contract analysis systems, yet providing that experience without exposing confidential information or risking conflicts is nearly impossible. Workflow optimization requires testing on realistic datasets to identify bottlenecks, but using actual client files for process improvement creates unacceptable risk.
Our datasets deliver measurable impact on your team's capabilities and operational efficiency:
Your firm needs to build internal tools, workflows, and AI capabilities that serve your clients' unique needs, but development requires data you don't have. Building custom document automation, matter management systems, or AI-assisted research tools demands realistic legal data for testing and validation. You can't use client files for development environments, the Enron data is a non-starter, and generic placeholder data fails to capture the complexity your tools must handle. You need specialized data that will enable the capabilities that set your firm apart.
Our datasets deliver measurable impact on your innovation capabilities and competitive positioning: