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AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
Case Study

AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm

DreamzTech built an AWS-native AI contract intelligence platform for a top-100 global law firm with 6 offices across the US and UK — replacing a 40-hour-per-contract manual review with Amazon Textract layout extraction, Anthropic Claude 3.5 Sonnet on Amazon Bedrock for clause reasoning, a custom Amazon SageMaker NER model trained on 45,000 anonymised prior contracts, and Amazon Kendra cross-contract search. The platform extracts 90+ clause types with 99.1% accuracy, reduces paralegal review time from 40 hours to 12 hours per contract, and recaptures $2.4M in annual billable hours.

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AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
AWS AI Contract Intelligence Platform Extracting 90+ Clause Types for Top-100 Global Law Firm
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AI Contract Intelligence on Amazon Textract + Amazon Bedrock (Anthropic Claude) — 70% Faster Contract Review for a Top-100 Global Law Firm

  • 1. AI contract intelligence platform on Amazon Textract + Anthropic Claude 3.5 Sonnet (Amazon Bedrock) for a top-100 global law firm with 6 offices
  • 2. Custom Amazon SageMaker NER model trained on 45,000 anonymised prior contracts — 99.1% clause-level accuracy across 90+ clause types
  • 3. Amazon Kendra-powered cross-contract semantic search and Amazon A2I paralegal review queues with explainable Claude reasoning traces
  • 4. Native integration with iManage Work, Aderant matter management and Microsoft Outlook contract intake
  • 5. 40 hours → 12 hours paralegal review time with $2.4M annual billable-hour recapture and 70% faster M&A due diligence

Overview

A top-100 global law firm with 6 offices across the US and UK needed to accelerate M&A due diligence and vendor-contract reviews. Manual paralegal review averaged 40 hours per contract — partners were billing $850/hour against work that could be automated. Dreamztech built an AWS-native AI contract intelligence platform on Amazon Textract for layout extraction, Anthropic Claude 3.5 Sonnet on Amazon Bedrock for clause-level reasoning, and a custom Amazon SageMaker named-entity recognition (NER) model trained on 45,000 anonymised prior contracts. The platform extracts 90+ clause types — from governing law to change-of-control, indemnity caps, liability limits and auto-renewal triggers — reducing paralegal review time from 40 hours per contract to 12 hours, with 99.1% clause-level extraction accuracy and $2.4M in annual billable-hour recapture.

Challenges

The firm faced critical operational and competitive pressure from in-house legal teams using AI contract review tools, plus growing M&A deal-flow that strained paralegal capacity across 6 offices.

  • 1. Average M&A and vendor-contract review of 40 hours per contract — paralegals stretched across 6 offices, partners losing high-value billable time to clause hunting
  • 2. 90+ clause types to extract per contract — governing law, indemnity caps, liability limits, change-of-control, auto-renewal, IP assignment, non-compete, MFN, exclusivity — none consistently captured by legacy keyword search
  • 3. In-house legal teams adopting AI contract review tools (Kira, ContractPodAI, Spellbook) — billable-hour erosion threatening 8% of M&A practice revenue annually
  • 4. 45,000 anonymised prior contracts in iManage Work — invaluable training data, but no model leveraging the precedent corpus
  • 5. Strict client confidentiality and conflict-of-interest constraints — generic SaaS contract AI tools could not be approved by the firm's information governance committee

How the AWS AI Contract Intelligence Platform Works

Dreamztech architected a production-grade AWS-native legal AI platform with five interconnected modules — from contract ingest to risk-flag dashboard — combining Amazon Textract layout extraction, custom Amazon SageMaker NER, Anthropic Claude on Bedrock for clause reasoning, Amazon Kendra for cross-contract search, and Amazon A2I for paralegal review.

  • 1. AWS Step Functions Orchestration — contracts ingested from iManage Work and Outlook into Amazon S3; Step Functions drives the multi-stage analysis pipeline with retry, idempotency and audit checkpoints
  • 2. Amazon Textract Layout Extraction — preserves clause numbering, defined-term tables, signature blocks and exhibit hierarchy; outputs structured JSON for downstream NER and LLM analysis
  • 3. Custom Amazon SageMaker NER + Anthropic Claude on Bedrock — SageMaker model identifies 90+ clause spans; Claude 3.5 Sonnet on Amazon Bedrock generates clause summaries, risk flags and reasoning traces with 200K-token context window for long agreements
  • 4. Amazon Kendra Semantic Search + Amazon A2I Review — paralegals query the 45K-contract corpus with natural language; A2I queues low-confidence clauses for human review with role-based access via AWS IAM Identity Center
  • 5. Risk Dashboard + Aderant Integration — clause findings flow into a partner-facing risk-flag dashboard; matter timekeeper credits flow back to Aderant matter management for billing and matter analytics

Solutions Delivered

Four integrated platform components were built and launched in a production engagement on AWS with SOC 2-aligned security, signed AWS BAA for client-confidential data handling, and seamless integration with the firm's iManage Work document management system.

Amazon Textract preserves the exact structural fidelity legal documents demand: clause numbering hierarchy (1.1, 1.1.1, 1.1.1(a)), defined-term tables, signature blocks with date and capacity attribution, exhibit and schedule cross-references, and footnote anchors. Textract Forms + Tables + Layout APIs run in parallel across the AWS Step Functions pipeline; structured JSON output preserves bounding-box coordinates so paralegals can click any extracted clause to jump back to the original PDF. Document hashes are written to AWS CloudTrail for tamper-evident audit.

We trained a custom Amazon SageMaker named-entity recognition model on 45,000 anonymised prior contracts from the firm’s iManage Work archive — labelling 90+ clause types including governing law, indemnity caps, liability limits, change-of-control, auto-renewal, IP assignment, non-compete, MFN, exclusivity and termination triggers. SageMaker hosts the model behind a private VPC endpoint. Anthropic Claude 3.5 Sonnet on Amazon Bedrock then generates clause summaries, risk flags and explainable reasoning traces — Claude’s 200K-token context window lets us analyse a 300-page master agreement in a single pass without chunking. The 99.1% clause-level accuracy is benchmarked against a held-out test set of 5,000 contracts.

The 45,000-contract precedent corpus is indexed in Amazon Kendra with custom legal-domain synonyms (“MFN” ↔ “most favoured nation”, “endeavours” ↔ “efforts”) so paralegals can ask natural-language questions (“show me all GDPR-aligned data-protection schedules signed since 2023”) and get ranked, citation-grounded answers in seconds. Amazon A2I human-review queues route low-confidence clauses (< 0.85 confidence on critical risk fields) and partner-flagged exceptions to senior associates for review. AWS IAM Identity Center enforces matter-level access control and Chinese-wall conflict-of-interest separation across the 6 offices.

Clause findings flow into a partner-facing risk-flag dashboard built on AWS AppSync + Amazon DynamoDB — partners see deal risk heat-maps, clause-level diffs against the firm’s playbooks, and recommended fallback positions for negotiation. iManage Work integration pulls source contracts into the pipeline and pushes annotated reviewed versions back as new document versions. Aderant matter-management integration captures timekeeper credits and matter-level analytics. AWS KMS customer-managed keys (CMK) encrypt every contract at rest; AWS CloudTrail provides an immutable audit trail covering every clause access, override, and partner approval — supporting the firm’s SOC 2, GDPR and SRA compliance posture.

Success Metrics

Measurable business outcomes validated in the first year post-launch — billable-hour data from the firm's Aderant matter-management system and clause-extraction accuracy benchmarks against a held-out test set of 5,000 contracts.

70%

Faster contract review cycle (40 hours → 12 hours per contract)

99.1%

Clause-level extraction accuracy across 90+ clause types

$2.4M

Annual billable-hour recapture redirected to high-value work

90+

Clause types extracted automatically (governing law, indemnity caps, change-of-control, auto-renewal)

45K

Anonymised prior contracts used to train the custom Amazon SageMaker NER model

6

Law-firm offices across US and UK on a unified AWS contract intelligence platform

Conclusion

DreamzTech delivered an AWS-native AI contract intelligence platform that replaced a 40-hour-per-contract manual review process with a 12-hour automated workflow. Amazon Textract layout extraction, Anthropic Claude 3.5 Sonnet on Amazon Bedrock for clause reasoning, custom Amazon SageMaker NER trained on 45,000 anonymised prior contracts, Amazon Kendra cross-contract search and Amazon A2I paralegal review combine into a single platform — extracting 90+ clause types at 99.1% accuracy and recapturing $2.4M in annual billable hours redirected to high-value M&A advisory work. Proof that purpose-built AWS AI contract intelligence beats both off-the-shelf legal SaaS tools and continued reliance on hourly paralegal review.
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Dreamztech delivers custom AI contract intelligence and intelligent document processing platforms for global law firms, in-house legal teams, M&A advisors and corporate counsel. AWS Partner, Microsoft Solutions Partner and Google Cloud Partner with 200+ AI projects across 15 countries and 97% client retention.

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    Talk to Our AWS AI Contract Intelligence Team

    Looking to build a custom AWS AI contract intelligence platform with clause-level extraction, Anthropic Claude reasoning, and integration with iManage Work, NetDocuments or Aderant? DreamzTech specialises in legal AI development on Amazon Textract, Amazon Bedrock and Amazon SageMaker — with signed AWS BAA, SOC 2-aligned security and matter-level access control via AWS IAM Identity Center.
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    Frequently Asked Questions (FAQ)

    Amazon Textract is the strongest hyperscaler service for preserving legal-document structure — clause numbering, defined-term tables, signature blocks and exhibit hierarchy survive intact through the Layout, Forms and Tables APIs. Anthropic Claude 3.5 Sonnet on Amazon Bedrock then handles the legal reasoning layer with a 200K-token context window — enough to analyse a 300-page master agreement in a single pass, no chunking, no lost cross-references. Claude is widely regarded as the strongest LLM for legal text given Anthropic’s Constitutional AI training. Running on Bedrock means the contract data never leaves the firm’s AWS account, under signed BAA, with full CloudTrail audit and KMS encryption.

    We trained a custom NER model on 45,000 anonymised prior contracts from the firm’s iManage Work archive — labelling 90+ clause types: governing law, jurisdiction, indemnity caps and exclusions, liability limits, change-of-control, auto-renewal, IP assignment, non-compete and non-solicit, MFN, exclusivity, termination triggers, force majeure, dispute resolution, GDPR data-protection, audit rights, insurance minima and more. SageMaker hosts the model behind a private VPC endpoint; clause spans flow into Anthropic Claude on Amazon Bedrock for summarisation, risk flagging and explainable reasoning. The 99.1% clause-level accuracy is measured against a held-out test set of 5,000 contracts.

    For this engagement we integrated with iManage Work (document management) and Aderant Expert (matter management and time-keeping). Across other DreamzTech AI contract intelligence engagements we have shipped integrations with NetDocuments, OpenText eDOCS, Microsoft SharePoint, Worldox, Elite 3E, Aderant Expert, ContractPodAI, Ironclad and direct Microsoft Outlook contract intake. All integrations use Amazon API Gateway with retry, idempotency keys and Amazon SQS for guaranteed-delivery messaging.

    Twenty-two weeks total. Phase 1 (Amazon Textract pipeline + custom Amazon SageMaker NER training on 45K contracts + iManage Work integration + go-live for 1 office) shipped in 14 weeks. Phase 2 (Anthropic Claude on Amazon Bedrock for clause reasoning + Amazon Kendra search + Amazon A2I review + Aderant integration + rollout to remaining 5 offices) added 8 weeks. The first useful capability — automated clause extraction on standard NDAs and MSAs — was in production by week 10, letting paralegals start saving billable hours while the more complex M&A clause types were still being trained.

    Within 12 months of go-live: paralegal review time dropped from 40 hours per contract to 12 hours (70% faster), 99.1% clause-level extraction accuracy across 90+ clause types, $2.4M in annual billable-hour recapture redirected to high-value M&A advisory work, 41% acceleration in M&A due-diligence turnaround, and a 22% increase in M&A deal capacity per partner. The model accuracy continues to improve as paralegal corrections feed back into a weekly Amazon SageMaker retraining job — protecting the firm’s billable-hour position against in-house legal teams using off-the-shelf AI contract review tools.

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