Buy vs. Build:  Why Companies Choose a Partner to Generate Document Information

Generative AI Execution Options

In today’s data-driven economy, the ability to unlock structured information from unstructured documents is no longer a luxury—it’s an efficiency imperative. From contracts and policies to statements of work and regulatory filings, vital business information is buried in PDFs, Word files, and scanned documents. The question facing many organizations isn’t whether to apply AI to generate this information, but how.

Companies often confront an execution fork in the road:

• Buy a specialized AI platform, purpose-built for document understanding at scale.
• Build their own in-house solution using general-purpose large language models (LLMs).

At first glance, building internally with the very visible LLMs may seem easy and cost-effective. But a deeper look reveals why more companies are turning to smaller proven platforms to fast-track results, reduce risk, save scarce resources, and scale intelligently.

The Myth of “Just Use an LLM”

It’s tempting to assume that an off-the-shelf LLM can simply be repurposed to extract data from your internal documents to automate a business process. After all, these models can read and summarize content, right?

Here’s the catch:
General LLMs aren’t trained to understand your domain-specific documents and your company’s own nuanced terminology or preferences. They may not extract precise structured and unstructured elements, and maintain auditability and consistency across thousands of pages. They likely don't automatically connect the data to your unique downstream databases or systems as the documents flow in. – a repetitive business process.

They are by nature driven by ad-hoc prompting, due to their consumer and search-centric origin. What they do is a far cry from a production-grade documents-to-data system, with human validation built-in.

Challenges of Building with General LLMs:

• Prompt Engineering Overhead: Custom prompts for every document type, use case, and data point are slow to build and maintain, and ‘ad-hoc’, rather than procedural.
• Data Governance & Compliance: Enterprises need transparency, explainability and traceability—often lacking in generic LLM outputs.
• Scalability Hurdles: Extracting from thousands of documents requires infrastructure, QA, validation, and exception handling.
• Hidden Costs: Time, people, and money spent on tools, infrastructure, and monitoring could be spent advancing true differentiators.

Focus Internal Resources Where It Counts: On Your Core Differentiation

Not all AI efforts are created equal. Smart companies recognize that internal teams should focus on AI initiatives that directly drive competitive advantage in their industry—not on building infrastructure or re-solving solved problems.

For example:

• Pharmaceutical companies can invest their internal AI resources into accelerating drug discovery and optimizing clinical trials.
• Insurance carriers can focus on building proprietary models to price risk more accurately using AI-driven underwriting.
• Retailers can apply AI to optimize dynamic pricing and supply chains.
• Every industry may have central focal points for applying AI talent and resources.

Building and maintaining an internal document data extraction system is a costly detour from these strategic priorities. The infrastructure, tuning, and compliance effort required is massive—and unnecessary when robust, proven platforms already put open-sourced and proprietary LLMs to use for this purpose and continuously invests to stay abreast of the ongoing advancements.

Why the ‘Buy’ Option Can Be the Smarter Move

Docugami is purpose-built to transform real-world complex business documents into structured, actionable data with speed and precision—so you don’t have to build and support the infrastructure yourself.

1. Built for Complex Documents

Docugami is optimized for domain-specific documents like YOUR legal agreements, contracts, policies, quotes, licenses, RFPs, NDAs, MSAs, SOWs, ACORD forms (like Loss Runs and SOVs), and most other document types, even totally unique ones to your business (and acronyms!). It captures:

• Contextual relationships across sections and pages
• Formatting variations and semantic inconsistencies
• Nested structures like clauses, tables, and conditional terms

Yes, most documents written and negotiated or edited by humans for business purposes are highly nuanced and variable.

2. Rapid Time-to-Value

Docugami delivers business results in weeks, not years:

• Automated classification documents of a type, created for a similar purpose
• A baseline of results for most document types
• No-code, business-user guided training or fine-tuning of your own models for variations
• Automation of document ingestion and output results
• Connectors and APIs to enable your unique business processes

3. Production-Ready Scalability

Process thousands of documents with ease, including:

• Built-in exception handling and data validation
• Direct integration into CRMs, Excel, databases, or analytics tools
• Monitoring and traceability of every document and data point

4. Compliance and Security You Can Trust

Especially in regulated industries like insurance, real estate, finance, life sciences and healthcare administration, Docugami provides secure, SOC2-compliant deployment.

5. Lower Total Cost of Ownership

Compared to building internally:

• Avoid deploying outsourced or internal data science or IT talent on document-understanding processes
• Eliminate hidden infrastructure costs
• Skip the endless maintenance treadmill

Benefit from Real, Proven Results

Organizations using Docugami report:

• 80%–95% or more reduction in manual data extraction and entry
  • Teams liberated from tedious copy-paste work
• Faster, higher-quality data access, decisions, and action
• Improved compliance and documentation auditability

Invent. Don’t Re-invent

In the AI era, the smartest companies are learning to invest and benefit in two fundamental ways:

1. AI for new business process efficiencies.
2. AI for what sets you apart.

They invest, but don’t reinvent tools that already exist. They do invent in areas where internal AI development can create proprietary advantages.

Let Docugami handle document data extraction—so your team can benefit from efficiencies in the AI industry’s continued innovation, while focusing your unique, scarce resources in proprietary work.

Unlock your documents. Unleash your data. Accelerate your business.
Choose Docugami—where AI meets the real world of business documents.