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CRUNCH is a Data Discovery service for document- and record-heavy work. Technology processes, searches, extracts, compares and cross-references material at scale; senior professionals define the question and scope, review findings and apply judgment. The result is usable work with material findings traceable to supporting records.

RelatedHow CRUNCH works

CRUNCH works through large bodies of material for Digital Due Diligence, Legal Data Services and Corporate Data Services. It starts with a defined question, uses technology for scale and speed, applies senior human review, and returns source-linked findings.

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No. CRUNCH is a service rather than self-service software. The client and CRUNCH agree the question and scope, the material is processed as part of the engagement, and senior professionals review findings before release.

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CRUNCH Data Discovery is used when a professional question depends on a large or fragmented body of records — for example due diligence, legal matters or corporate data review. Technology supports scale and speed; senior professionals provide review and judgment; output remains traceable to source.

RelatedHow CRUNCH works

CRUNCH is presented as a Data Discovery service rather than a self-service software license. It combines technology-assisted document and data work with senior professional review for Due Diligence, Legal Data and Corporate Data engagements.

RelatedWhat CRUNCH does

CRUNCH Data Discovery is the process of finding and connecting useful information inside client-provided or agreed sources. The goal is to identify records, relationships, exceptions and gaps that answer a defined question and preserve a path back to source.

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At CRUNCH, data is not limited to spreadsheets. It can be a contract, email, PDF, ledger record, schedule, corporate document, timeline or other structured or unstructured material. Data Discovery connects those records to the question being asked and preserves a path back to source.

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Start with the question, then make the relevant sources searchable and comparable through processing, retrieval, extraction and classification. Connect entities, events and related records, surface exceptions and gaps for review, and keep source facts distinct from interpretation.

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Data is the source material. Data Discovery is the process of locating what matters inside that material, connecting records and entities, identifying exceptions or gaps and preserving traceability to the source of truth. CRUNCH applies that process across Due Diligence, Legal Data and Corporate Data Services.

RelatedHow CRUNCH works

CRUNCH follows four stages: define the question, relevant material and deliverable; process, search, extract and cross-reference the records; apply senior professional review and judgment; then return usable work with source, analysis and open questions distinguishable.

RelatedHow CRUNCH Works

The client provides the material relevant to the question — for example a transaction data room, case documents and correspondence, or corporate contracts and reports — plus the questions the review must answer.

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Scope is agreed with the client around the decision or question the work must support. Senior CRUNCH professionals translate that into operational review scope: sources, issues, comparisons and deliverable.

RelatedHow CRUNCH Works

CRUNCH delivers reviewed work rather than raw model output: findings, exceptions, inconsistencies, gaps or chronologies depending on the engagement. Material findings retain a path back to supporting records.

RelatedHow CRUNCH Works

Digital Due Diligence is due diligence in which technology supports large-scale processing, search, extraction, comparison and cross-referencing of transaction material alongside professional human review. It changes how document work is performed, not the need for judgment.

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The transaction team supplies the data room and its questions. Scope is agreed first; technology classifies and processes documents, extracts material terms and compares related records; senior professionals review the results. The output is a source-linked set of risks, inconsistencies and gaps.

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Typically the client provides the data room and transaction questions. Material may include contracts and amendments, governance records, correspondence, financial statements and schedules. The exact set depends on transaction scope.

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A linear review progresses mainly document by document. A technology-assisted workflow can index, classify, search, extract, compare and cross-reference large groups of records before and during human review. The difference is operating architecture and scale.

RelatedDigital Due Diligence

Due diligence is the structured review performed before a transaction or decision to understand the target, rights, obligations, contracts, financial information, risks and gaps within an agreed scope. CRUNCH focuses on the underlying data and document-review layer.

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The business objective is similar: understand the target and the transaction risks. Digital Due Diligence describes a workflow where technology supports processing, search, extraction, comparison and cross-referencing at scale alongside human review and professional judgment.

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Due diligence gives M&A lawyers a structured factual and documentary basis for evaluating terms, obligations, inconsistencies, exceptions and information gaps. CRUNCH can support the document/data review layer; legal interpretation and transaction advice remain with counsel.

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Data and technology can turn a large data room into a processable corpus through indexing, retrieval, extraction, classification, comparison and cross-referencing. The goal is to reach relevant material and relationships more efficiently, not to replace the transaction team's judgment.

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M&A due diligence is the pre-transaction review used to understand a target company's rights, obligations, contracts, governance, financial information, disputes, risks and information gaps within an agreed scope. CRUNCH supports the data/document-review layer and source traceability.

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There is no universal duration. Timing depends on volume, complexity, data-room quality, scope, review questions and transaction deadline. CRUNCH agrees timing per engagement and does not publish a one-size-fits-all SLA.

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CRUNCH does not state a fixed duration for every transaction. Timing is scoped against document volume, file types, questions and deadline. Processing, search and comparison need not rely solely on sequential reading; senior review remains part of release.

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Technology can process, classify, search, extract, compare and cross-reference transaction records across a large data room and concentrate relevant material for review. This can reduce repetitive document work while professionals still define scope and assess findings.

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It can shorten parts of document work when volume is substantial because processing and retrieval do not have to be purely linear. There is no universal time ratio; data quality, file types, scope and human review still matter.

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A time-critical acquisition is a relevant use case because CRUNCH is designed around defined scope, large document sets and deadlines. Feasibility and timing must still be assessed against the actual data room and questions; no public fixed SLA is implied.

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Not necessarily. Technology can reduce repetitive manual work and expand comparison and cross-referencing while professional reviewers still assess findings. Scope, missing records and unresolved questions should remain explicit.

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A review can be designed around an external deadline when the question, source set, priorities and deliverable are fixed early. Technology can help manage scale, but feasibility must be assessed per engagement.

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Linear review allocates human attention item by item. A technology-assisted workflow can build an index, classify, retrieve, extract and compare records across the corpus before directing human attention to relevant issues.

RelatedDigital Due Diligence

Time-critical due diligence is a transaction review performed against a compressed decision or signing timeline. The answer is not simply to read faster: the team must prioritize scope, process the record set efficiently, surface material issues early and preserve human review. Feasibility still depends on the actual data room.

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There is no standard duration for due diligence. Timing depends on the size and complexity of the transaction, the volume and quality of the Data Room, the types of documents involved, the questions within scope, and the transaction deadline. In a traditional review, substantial time can be spent working through documents sequentially. At CRUNCH, technology supports processing, search, extraction, classification, comparison, and cross-referencing across large volumes of material, helping relevant information and potential issues reach reviewers more efficiently. Speed does not replace professional review. Senior professionals define the scope, review the findings, and apply judgment, while material findings remain connected to their supporting source documents for verification. Technology can therefore reduce document-intensive work and enable due diligence to operate at a scale and pace that is difficult to achieve through linear review alone — without removing human review from the process. Actual timing is determined for each transaction based on its scope and materials; CRUNCH does not claim a fixed timeline or universal SLA.

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Data Room Review is systematic work on a transaction data room: organizing and classifying documents, extracting material terms, comparing agreements with amendments and schedules, connecting disclosures and correspondence, and identifying risks, inconsistencies and missing information.

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Start with clear scope, then process and classify the source set, extract key terms, connect versions and amendments, and run comparisons around transaction questions. Human reviewers can then focus on findings and exceptions.

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No. Broad coverage can surface relationships a sample may miss, but it is not a guarantee of completeness. The review should state scope, missing records and unresolved questions.

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A virtual data room review is the structured examination of documents made available for a transaction or diligence process. Review typically involves organizing the source set, identifying material agreements and amendments, comparing records, tracking missing information and surfacing issues for the deal team.

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At that scale, sequential reading alone is not a practical architecture. A technology-assisted workflow can use indexing, classification, search, extraction, grouping or deduplication where appropriate, followed by human review against scope.

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Use layered retrieval rather than one keyword query: indexing and normalization, entity and term search, extraction of key fields, grouping of related records, and comparison of versions or amendments. Human reviewers then test the surfaced material against the actual question.

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CRUNCH Legal Data Services work on the records behind a legal matter: documents, correspondence, evidence and prior work product. Material is organized and searchable, chronologies and connections are built, key records and inconsistencies are surfaced, and findings remain linked to source.

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Keyword search can be useful, but it does not by itself connect versions, events, people and correspondence. A legal team may also need chronology building, cross-document comparison, contradiction mapping and source traceability.

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CRUNCH processes and organizes the source set, then connects events, people, dates and related records into a working timeline. Material entries retain a path back to supporting documents so lawyers can verify the record.

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Data services for lawyers turn documents, correspondence and evidence into searchable, connected material: facts, timelines, entities, exceptions, inconsistencies and source-linked findings. Technology expands scale; lawyers retain legal judgment and responsibility.

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No. CRUNCH performs material-intensive work such as processing, organization, search, extraction, comparison and source linking. Legal interpretation, advice, strategy and professional decisions remain with lawyers.

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No. Technology performs scale-intensive processing, search, extraction, comparison and cross-referencing, but people define the question and scope, review findings and decide what is released.

RelatedHow CRUNCH Works

Senior professionals review findings within the agreed scope. Their role is to assess context, significance, contradictions and unresolved questions and determine what is appropriate to release.

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Relevance and materiality depend on the question, context and purpose. NIST has noted that characteristics of AI trustworthiness involve human judgment and cannot be reduced to a single metric.

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No. CRUNCH can organize, search, connect and flag exceptions in client-provided records, but engagement procedures and professional conclusions remain the accounting firm’s responsibility.

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Use technology to reduce repetitive work and concentrate relevant material, while keeping scope, review and professional decisions with people. Speed comes from the workflow architecture — not from assuming every model output is correct.

RelatedHow CRUNCH works

CRUNCH Corporate Data Services use records an organization already holds to answer a defined business, management, compliance, contract or investigation question. Sources are organized around that question and exceptions, inconsistencies and gaps are returned with traceability.

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Enterprise information is spread across systems, formats, contracts, reports and correspondence, and storage does not automatically make it usable for a decision. Splunk and Seagate/IDC provide market-level context, not measurements of a CRUNCH client.

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The starting point is a business question, not a dashboard or dataset. Scope is built around records that can answer that question, and the output is a set of traceable findings and gaps.

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Technology-Assisted Review, or TAR, refers to review workflows in which technology helps classify, prioritize or identify documents for human review. The term predates generative AI. Research on particular TAR processes is not a performance claim for every system or CRUNCH.

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TAR stands for Technology-Assisted Review. Technology helps organize, classify, prioritize or retrieve relevant material within a broader review process. TAR is not synonymous with ChatGPT or generative AI.

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Yes. Technology-Assisted Review and computer-assisted review were used and studied in e-discovery well before the generative-AI wave. Grossman and Cormack published their widely cited paper in 2011 using TREC 2009 data.

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No. TAR describes a review workflow; generative AI is a model category that may be used for extraction, synthesis or question answering. Evaluation should focus on method, sources, controls and human oversight.

Grossman and Cormack analyzed TREC 2009 results and reported that two technology-assisted processes outperformed an exhaustive-manual-review benchmark on studied measures. The finding is study-specific and is not evidence of CRUNCH performance.

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A source-linked finding is a finding that retains a path back to the underlying record supporting it — for example a document, clause, message or row. The point is to let the user inspect the source of truth.

RelatedHow CRUNCH Works

Open the record linked to the finding, check what the source actually supports, and distinguish source material from analysis and unresolved questions. That is the practical purpose of traceability.

RelatedHow CRUNCH Works

The live CRUNCH site states that material findings retain a path back to supporting records. The implementation should preserve that bounded claim rather than turn it into an absolute promise about every output element or file type.

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The source of truth is the original record on which a statement depends: the agreement, amendment, email, report, filing or data row. A material conclusion should be checkable against the underlying record.

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Traceability supports review, challenge and correction. A lawyer, accountant, executive or committee can see which record supports a finding and distinguish evidence from interpretation or an open question.

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The evidence pack provides several forms of context: RAND on limits to increasing review speed, Consilio on reviewer divergence and EDRM on document-review cost. These sources do not measure CRUNCH and do not support a blanket claim that human review is poor.

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The lawyer should be able to follow the source path from a material finding back to the supporting document, clause, message or record, inspect the context and apply independent legal analysis. Source linking makes the finding reviewable rather than authoritative by default.

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CRUNCH takes on document-intensive material work — organization, search, review support, chronology building and source-linked findings — so lawyers can spend more time on legal analysis, strategy and advice.

RelatedCRUNCH for Law Firms

Additional reviewers add capacity, but also hours, coordination and potential reviewer variation. EDRM, Consilio and RAND provide context on cost, divergence and review-speed limits; they do not measure a particular team or CRUNCH.

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CRUNCH can take on the material-intensive layer — organization, search, extraction, comparison, chronology and source linking — so the lawyer can focus on legal analysis, strategy and advice. CRUNCH does not replace the lawyer or provide legal conclusions on the lawyer's behalf.

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CRUNCH organizes, searches and connects client-provided records in document-heavy engagements — contracts, ledger records, schedules, confirmations and prior files — and flags exceptions, inconsistencies and gaps. The accounting firm owns procedures and conclusions.

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Professional conclusions depend on the information underneath them. In its US auditing context, PCAOB AS 1105.10 addresses testing accuracy and completeness of company-produced information used as audit evidence. Applicability varies.

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No. CRUNCH can prepare organized, searchable, source-linked material and flag exceptions or missing information, but audit procedures and conclusions remain with the accounting firm.

RelatedCRUNCH for Accounting Firms

Data services for accounting firms organize and connect records that support professional engagements — contracts, ledgers, schedules, confirmations and prior files — to surface exceptions, inconsistencies, missing information and source relationships. Professional procedures and conclusions remain with the accounting firm.

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CRUNCH supports document-heavy work behind investment, financing and risk decisions: data rooms, agreements, disclosures, compliance records and related material. Technology helps process the record; the institution and its advisers make the decision.

RelatedCRUNCH for Financial Institutions

A material issue may be spread across an agreement, amendment, schedule, disclosure and another record. Under a deadline, the challenge is connecting versions and spotting conflicts, not merely reading faster.

RelatedCRUNCH for Financial Institutions

CRUNCH supports legal, compliance, risk and management teams when a business question depends on a large record set. The engagement scopes relevant sources, connects records and entities, surfaces exceptions and returns findings with a path back to source.

RelatedCRUNCH for Corporations

Data availability is not data usability. Records may sit across systems, formats and owners with no fast way to connect them to the management question. Dark-data surveys are market context, not a diagnosis of a specific organization.

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When a board question depends on a large record set, the work can be scoped around relevant sources, connected across entities and events, and returned as traceable findings and gaps. That creates an organized factual basis; board judgment and legal advice remain separate.

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The live site states that the client platform is invite-only, matter access is limited to people working on the engagement, uploaded files are scanned before opening, and a retention policy is published. Do not expand these into unverified certification claims.

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AI Due Diligence is a broad search term for due-diligence workflows that use AI or machine-assisted review in part of the document work. For CRUNCH, the useful description is technology for scale, senior human review for judgment, and source-linked output for traceability.

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No. No review method should be described as guaranteeing every risk will be found. Results depend on available records, scope, questions, method and human review; missing records and unresolved questions should remain visible.

RelatedDigital Due Diligence

CRUNCH uses technology within a broader review workflow: large-scale processing and retrieval, extraction and comparison, human review and source-linked findings. The useful model is technology-assisted professional work, not an autonomous chatbot answer without verification.

RelatedHow CRUNCH works