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IBM Commercial and Professional Services Poland

LDS Łazewski Depo & Partners

Document Processing · Enterprise Knowledge Search

LDS needed to reduce the time, cost and risk involved in manual patent searches and drafting work so its attorneys could protect clients' intellectual property more efficiently without sacrificing accuracy or data security.

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over 40 IP professionals

Reported impact

Business outcome

LDS reduced time spent on manual IP work, improved confidence in search results, and created a path to handle more matters while keeping attorneys focused on higher-value strategic and technical work.

  • Customer Experience
  • Productivity Improvement
  • Speed to Market

Solution

LDS worked with IBM and partner nFlo to adopt PatentPro AI, a solution built on IBM watsonx.ai for patent-search and drafting workflows. Attorneys can now describe inventions in natural language instead of manually querying and reviewing large patent datasets, and PatentPro AI uses API integrations to surface relevant patents with confidence scores. Because the firm handles commercially sensitive client information, the solution was also designed with strong information-security and data-governance controls rather than treating generative AI as an isolated experiment. The same platform is being extended beyond search into drafting support, where shorter attorney inputs can be expanded into fuller application drafts for human review. This makes watsonx.ai the reasoning layer for both retrieval and content creation, giving LDS a practical AI tool that shortens research-heavy legal work while keeping professionals in control of final filings.

Data flow

Attorneys describe inventions in natural language, PatentPro AI queries patent sources through API integrations, watsonx.ai returns ranked patent results with confidence scores, and the same platform can expand shorter attorney inputs into draft applications for review.

Solution architecture

1 components · 1 layer
  1. Compute
    • IBM watsonx.ai Powers PatentPro AI for natural-language patent search, confidence-scored retrieval and draft-generation support.

Architecture clues

  • Security and data governance were built in because the firm handles commercially sensitive information.
  • The platform is being extended from search into draft patent application generation.
  • The search workflow uses natural-language prompts plus API integrations to retrieve patent results.

Evidence from the source

"LDS plans to pilot PatentPro AI for drafting"
"attorneys could describe inventions in natural language and let PatentPro AI use API integrations to surface relevant patents complete with confidence scores"
"incorporated strong client information security and data governance capabilities"
"their team of over 40 professionals"
"using the IBM watsonx.ai studio"
Transparency Evidence & methodology 70/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value70/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. IBM

    LDS Łazewski Depo & Partners customer story

    First-party
    https://www.ibm.com/case-studies/lds
    Source type
    Vendor-published customer story
    Published
    Dec 9, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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