Move your team from Everlaw to Kira.
Each person gets a short interview, then a personalized step-by-step guide showing exactly where their saved work, prompts, and projects land in Kira — and the few things that need a manual step, walked through. You send one invite; nobody becomes the help desk, and nothing in Everlaw is changed or cancelled. Want to see where you’re paying for both first? Run the free audit.
Both tools let reviewers ask natural-language questions across a large document corpus and receive extracted answers without writing search queries. In Everlaw this is Deep Dive (ask a question; get cited answers from millions of docs) and Review Assistant (per-document Q&A and summaries). In Kira it is Generative Smart Fields (type a plain-English question per field; Kira returns answers extracted from each contract in the project). To migrate a workflow from Everlaw to Kira: export your Deep Dive query templates as a reference list, recreate each as a Generative Smart Field question in a Kira project (no prior training needed), and ensure the project's GenAI toggle is enabled by your admin. Going the other direction, map each Kira Generative Smart Field question to an Everlaw Review Assistant prompt or a Deep Dive query; upload the same document set to Everlaw and run batch summaries/extractions from the AI menu. History (prior answers, annotations) does not migrate automatically in either direction — export Kira's Analysis Grid to Excel or Everlaw's batch extraction results to CSV before switching.
- Warning: Everlaw batch AI operations (batch summaries, batch custom extractions) consume purchased credits on top of the base subscription; single-document AI is included. Kira's Generative Smart Fields require the GenAI toggle to be on — admins can disable it per project for matters where generative AI is contractually prohibited.
- Warning: Everlaw's Deep Dive queries the full litigation document corpus (emails, deposition transcripts, etc.); Kira's Generative Smart Fields are built for contracts and transactional documents. Cross-document types are handled differently and query results are not directly comparable.
- Warning: Neither platform exports its AI query history in a format the other can natively import — plan to rebuild your question library from scratch on the receiving side.
Both platforms provide a generative AI layer that produces summaries of individual documents and allows follow-up questions with citations back to the source text. In Everlaw this is Review Assistant: open any document and ask questions or request a summary; answers are grounded in that document's content. In Kira this is Chat and Smart Summaries: when GenAI is enabled on a project, reviewers ask questions about specific documents or across a portfolio and receive cited excerpts so every answer is verifiable. Migrating from Everlaw to Kira: recreate your Review Assistant summary templates as Kira Smart Summary configurations in the project settings; upload the documents and run Smart Summaries. Going from Kira to Everlaw: upload the same contracts, then use Everlaw's Review Assistant per document or Deep Dive for cross-document queries. Prior conversation history and generated summaries are not exportable in a structured format by either tool — save outputs to PDF or copy key summaries to a shared document before switching.
- Warning: Kira's Chat and Smart Summaries require the project-level GenAI toggle to be enabled by an admin; this can be disabled on a per-matter basis for governance reasons. Everlaw's Review Assistant is governed by the EverlawAI credit system for batch operations, with single-document use included in the base subscription.
- Warning: Kira's chat responses include inline citations to contract text, which supports audit trails in regulated transactions. Everlaw's Review Assistant provides grounded answers within the platform but the citation display format differs — verify the output format meets your client reporting standards before switching.
- Warning: Neither platform exports AI chat transcripts or generated summaries in a machine-readable format that the other can import. Download summaries as part of your offboarding checklist.
Both platforms let reviewers search across an uploaded document corpus without knowing the exact keywords in advance. Everlaw's document review interface supports nearly instantaneous full-text search across processed documents, with batch redaction and automated first-pass classification built in. Kira's Concept Search lets users type a legal concept (e.g., 'change of control', 'indemnification cap') and find relevant passages across all contracts in the project — no model training or Smart Field setup needed, and it remains available even when the GenAI toggle is off. To move a search-driven review workflow from Everlaw to Kira: export the document set from Everlaw (download originals), create a new Kira project, bulk-upload the contract files, and use Concept Search to recreate ad hoc queries. To move from Kira to Everlaw: export originals from the Kira project, upload to Everlaw for processing (up to 1 million docs/hour), then use Everlaw's search interface. Annotations, redactions, and reviewer notes made in one platform do not carry over to the other.
- Warning: Everlaw processes heterogeneous document types (email, PDFs, audio, video) and includes batch redaction; Kira Concept Search is designed for contract documents and does not offer redaction. A litigation team will find Everlaw's review toolset much broader.
- Warning: Everlaw includes unlimited user licenses on all plans, so adding co-counsel or clients costs nothing extra. Kira's seat model is not publicly disclosed — confirm user-count pricing before migrating a large team.
- Warning: Kira Concept Search operates independently of the GenAI toggle and requires no configuration, making it faster to use for one-off searches; Everlaw's equivalent (Deep Dive) requires EverlawAI credits for batch operations.
Both tools apply machine-learning classification to large document sets to surface relevant content without manual review of every page. Everlaw's predictive coding trains a relevance model from a seed set of reviewer decisions and then ranks the remaining corpus; Kira's clause extraction runs 1,400+ pre-trained AI models against uploaded contracts to surface specific clause types with 90%+ accuracy. Migrating from Everlaw to Kira: the use case shifts — predictive coding for litigation relevance ranking has no direct Kira equivalent, but if the goal is to identify specific clause types across a contract portfolio, upload the contracts to a Kira project and let the extraction models run automatically with no training required. Going from Kira to Everlaw: if you need to rank litigation documents for relevance, import into Everlaw and run a predictive coding workflow by coding a seed set (typically 50–200 documents); clustering tools in Everlaw help group similar documents to accelerate seed-set selection. Reviewer coding decisions (the training labels) from either side do not transfer — the models are product-specific.
- Warning: The underlying tasks differ in scope: Everlaw predictive coding targets litigation relevance classification across heterogeneous document types; Kira clause extraction targets contract clause identification in transactional documents. A buyer doing both litigation and contract work will likely need both tools rather than treating them as full substitutes.
- Warning: Everlaw predictive coding is included in all platform plans at no extra cost. Kira's pricing is not publicly listed — clause extraction capacity and model access depend on the contracted Kira/Litera plan.
- Warning: Everlaw requires a human seed set to train the model (minimum coding session before the classifier is useful); Kira's pre-built models run immediately with no training data required from the buyer.
Both platforms target enterprise legal teams with SOC 2 Type II certification and GDPR alignment as baseline requirements; assessing security posture before switching between them involves comparing the specific certifications each holds and confirming data-residency options match your firm's requirements. Everlaw holds SOC 2 Type II (with HIPAA), FedRAMP Moderate, GovRAMP Moderate, ISO/IEC 27001:2022, ISO/IEC 27017, ISO/IEC 27018, Cyber Essentials Plus, and Data Privacy Framework. Kira (via Litera) holds SOC 2 Type II and SOC 3, with GDPR/DORA/NIS2 alignment and multi-region data residency (US, Canada, EU, APAC). When migrating from Everlaw to Kira: confirm with Kira/Litera which data-residency region your project will be hosted in; verify whether your firm's FedRAMP or government compliance requirements are met (Kira does not publish a FedRAMP authorization). When migrating from Kira to Everlaw: confirm GDPR/DORA data residency in the Everlaw contract (Everlaw is GDPR-listed but residency specifics should be confirmed with their team). Both platforms support SSO and MFA. Neither stores client contract data to train their AI models.
- Warning: Everlaw holds FedRAMP Moderate and GovRAMP Moderate authorizations — relevant for US government and defense-sector matters. Kira/Litera does not publicly list FedRAMP authorization; government-regulated buyers should confirm before migrating from Everlaw to Kira.
- Warning: Kira offers GDPR/DORA/NIS2 alignment and regional data residency options across US, Canada, EU, and APAC — specifically useful for EU-regulated transactions. Everlaw's regional data residency options should be verified directly with Everlaw for non-US matters.
- Warning: Kira's GenAI toggle can be disabled per project by an admin, ensuring that generative AI is never applied to matters where AI use is contractually or ethically restricted. Everlaw manages AI credit consumption at the account level rather than offering a per-matter AI disable toggle.