Blog

Solve Intelligence is pleased to announce a strategic partnership with HGF, one of Europe’s leading intellectual property firms. The collaboration is focused on a clear objective: customising AI-driven drafting workflows to meet the specific needs of HGF and some of its clients.

Rather than adopting a one-size-fits-all approach, HGF is working closely with Solve Intelligence to shape how the drafting platform behaves across different technologies, client preferences, and drafting styles. The built-in, customisable features available in Solve’s platform are what makes this possible.

"We evaluated the field carefully before committing. Solve Intelligence delivered the drafting quality our attorneys demand and integrated seamlessly into how they already work. We are investing in the foundation for HGF's future practice."

Richard Hodkinson, Chief Technology Officer at HGF

Solve Intelligence participated as a sponsor of FICPI’s ABC Meeting 2026 in Nashville, with CEO and Co-founder Chris Parsonson, demonstrating the practical application of a purpose-built patent AI platform. Patent attorneys and litigators convened for a key session addressing a central question: what is required for AI to be ready for patent practice? 

Key Takeaways:

• Solve Intelligence supports the full patent lifecycle across 700+ IP firms, from invention disclosure through litigation.
• One firm that adopted Solve Intelligence mid-fiscal year exceeded its billing targets by $1 million by reallocating AI-saved time to higher-value work.
• In-house teams now require outside counsel to use AI tools, making AI fluency a firm selection criterion rather than a differentiator.
• Attorneys report that ROI is not simply about increasing speed, but about reallocating the time saved to higher-value strategies, cross-sell analysis, and client insights.

Solve Intelligence cuts the time attorneys spend on patent work by half. This lets a solo practitioner or small patent firm widen their offering without widening headcount. Work that a small practice once had to outsource can now be brought in-house, including creating patent drawings and prior art searching. The results are faster turnaround and higher margins for small firms. These time savings also free up capacity to offer ancillary services like landscaping, freedom-to-operate analysis, and infringement detection, work that was historically hard to do for small firms because of the manual effort involved.

Key Takeaways:

• AI lets small firms bring outsourced work back in-house, including patent drawings and prior art search, improving margins and shortening turnaround.
• AI makes patent attorneys more productive, freeing capacity for landscaping, FTO, and infringement detection work.
• Patent work is structurally complex, so purpose-built patent AI, not a general chatbot, is what delivers reliable output.

Founded in Malmö over three decades ago, Hansson Thyresson has built its reputation on close client relationships paired with deep technical and legal expertise. When the firm decided to integrate AI into its practice, it looked for a platform that could deliver enterprise-grade capability. They chose Solve Intelligence.

Key Takeaways:

• Hansson Thyresson has adopted Solve Intelligence for patent application drafting, bringing enterprise-grade AI into the firm's workflows.
• The firm pairs Solve Intelligence with its hands-on, attorney-led service model, keeping practitioners in control of every output.
• For Hansson Thyresson, Solve Intelligence amplifies attorney expertise, improving work quality and focus on strategic work that matters most to clients.

Solve Intelligence has teamed up with LexisNexis^® Intellectual Property Solutions to bring global patent litigation insights into Solve Intelligence workflows for patent drafting, prosecution, claim charting, freedom-to-operate assessments, invalidity analysis, and related IP work.

R&D teams use patent landscape analysis to locate uncharted areas of a technology field, assess freedom-to-operate (FTO), and focus development resources on the areas of highest commercial value and broadest potential claim coverage.

Key Takeaways:

• A patent landscape search locates whitespace; a novelty search locates prior art blockers. 
• Patent landscape outputs require contextual analysis; volume alone does not determine opportunity or density.
• Solve’s Charts tool scans millions of patents from a single file upload and leverages agentic searching, replacing manual iterative keyword & semantic search.

At IPBC Global 2026, Solve Intelligence was proud to be a sponsor of the conversations shaping the future of intellectual property. At the conference, we demonstrated how our platform amplifies end-to-end patent workflows, including licensing, litigation, and IP-backed finance.

Key Takeaways:

• Generic LLMs cannot perform the structured legal reasoning and claim analysis that patent licensing and litigation require.
• AI lowers the cost of analysing portfolios, from claim-to-product mappings to validity analyses, accelerating both sides of licensing negotiations.
• IP-backed finance, insurance, and M&A due diligence are growing in sophistication and volume.
• The profession faces a capacity gap that generic AI tools are not designed to close.

A freedom to operate (FTO) analysis is a claim-by-claim assessment of whether a commercial activity would infringe any third-party patents in the markets where it will take place. AI speeds it up by handling the parts that scale badly by hand: surfacing relevant patents, mapping product features against claims element by element, pulling legal status by jurisdiction, and producing a cited, structured draft for the attorney to review and refine.

Key takeaways

• FTO analysis determines whether a product infringes third-party patents.

• A valid patent on your own invention doesn’t guarantee freedom to operate.

• AI compresses the slowest stages of FTO, including search, triage, and element-by-element claim mapping, while the attorney retains the legal judgment and owns the opinion.

• Generalist AI and purpose-built patent tools share a surface format; but FTO reliability depends on integration, not interface.