# M-Son IP

> M-Son IP is a boutique patent research and IP services firm with teams in Chicago, USA and Hyderabad, India. Every service (prior art searches, freedom to operate, patent landscapes, claim charts, portfolio analysis, patent drafting and more) is offered as AI Only, AI + Expert or Expert Only, with subject-matter experts guiding and checking AI work at every stage. M-Son IP has delivered hundreds of projects since 2009.

- Website: https://www.mson-ip.com
- Email: sales@mson-ip.com
- Phone: +1 (708) 852 5645 (Chicago, USA), +91-988-503-4635 (Hyderabad, India)
- Founded: 2009

## How we work

- AI Only: Automated research for early exploration and screening. Findings need further review. Best for: Early idea checks and screening, Internal R&D awareness, High-volume, low-stakes questions. Turnaround: 1 to 2 business days.
- AI + Expert: AI-assisted research with expert direction, analysis and validation throughout. Our subject-matter experts check the quality at every stage and guide the AI to the right output. Review depth fits your service, technology and decision. Best for: Filing and launch decisions, Licensing, litigation support and due diligence, Most patent and product research. Turnaround: AI stage: 1 to 2 business days. Expert review: 2 to 3 days.
- Expert Only: Research and analysis done entirely by our subject-matter experts with conventional research tools. Best for: Clients, courts or policies that restrict AI use, Work that needs fully manual analysis, Highly confidential matters kept off AI tools. Turnaround: Set in your proposal.
- AI processes the information; experts make it relevant. Our experts define the approach, review findings at every stage, verify every source and sign off. An AI-generated answer can look complete even when it isn't; recording what was covered is how clients know what an answer leaves out.

## Services

- Patentability search (Prior art searches; modes: AI Only, AI + Expert, Expert Only): Know whether your invention is new before you spend on filing.
- Invalidity search (Prior art searches; modes: AI Only, AI + Expert, Expert Only): Find the references that can knock out an asserted or blocking patent.
- Freedom to operate (Prior art searches; modes: AI Only, AI + Expert, Expert Only): Launch with a clear view of the in-force patents in your way.
- State of the art search (Prior art searches; modes: AI Only, AI + Expert, Expert Only): See how far a technology has already advanced, before you invest in it.
- Sequence search (Prior art searches; modes: AI Only, AI + Expert, Expert Only): Find every patent and publication that discloses or claims your biological sequence.
- Chemical structure search (Prior art searches; modes: AI Only, AI + Expert, Expert Only): Find compounds identical or similar to yours, including those hidden in Markush claims.
- Patent landscape (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): One study that helps your research, legal and business teams at once.
- Competitive intelligence (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): See what competitors protect, where they are heading, and who they are buying, before it shows up in their products.
- Product improvement (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Use the solutions already in the patent record, from your field and parallel industries, to improve your product faster.
- Risk monitoring (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Know when a new patent or lawsuit could affect your products, while there is still time to act.
- Claim charts (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Map every element of a claim to a product, a standard or prior art, with evidence that holds up.
- Problem-solution analysis (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Map every problem in a technology to the solutions already proposed.
- White space analysis (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Find the areas with little patent protection and real business opportunity.
- Licensing in/out (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Find the patents worth licensing in, and the companies most likely to license yours.
- Open innovation (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Find the right external partners with solutions you don't yet know about.
- M&A analysis (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Pick the right target and know its patent risks before the deal closes.
- Technology transfer (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Help universities and labs decide which inventions to file, and find the companies that will license them.
- Inventor intelligence (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Find the inventors behind a technology, what they work on, who they work with, and where they move.
- Instant novelty search (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): A fast first read on whether an idea is new, so you know whether to invest in a full search.
- Global patent protection strategy (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Decide where to file, based on your business, budget and timeline.
- Attorney intelligence (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): See which firms and attorneys work in your technology, for whom, and with what results.
- Claim rejection analysis (Landscapes and multi-purpose studies; modes: AI Only, AI + Expert, Expert Only): Learn how examiners reject claims in your field, and which arguments and amendments get them granted.
- Patent drafting (Patent protection; modes: AI + Expert, Expert Only): Claims drafted for the broadest defensible scope, from your disclosure.
- Patent illustrations (Patent protection; modes: AI + Expert, Expert Only): Patent drawings that meet the formal rules of each patent office.
- Patent filing (Patent protection; modes: AI + Expert, Expert Only): Filing, IDS and paralegal support, so deadlines are never missed.
- Office action response (Patent protection; modes: AI + Expert, Expert Only): Technical and legal arguments that work together to overcome rejections.
- Filing strategy (Patent protection; modes: AI + Expert, Expert Only): Decide which inventions to file, where, when and through which route, based on evidence.
- Licensing study (Patent monetization; modes: AI Only, AI + Expert, Expert Only): Use patent data to find licensing, alliance and acquisition opportunities.
- Claim charts / infringement analysis (Patent monetization; modes: AI Only, AI + Expert, Expert Only): Find the products and standards that may be infringing your patents.
- Patent portfolio study (Patent monetization; modes: AI Only, AI + Expert, Expert Only): Turn portfolio spoilage into savings and new revenue.

## Tools (delivered as AI + Expert services)

- Technology Monitoring & Risk Assessment Platform: Send us your products and technology. Our AI and experts watch new patents, score the risk, and deliver the results to your technical and legal teams in a secure workspace.
- Chemical Patent Analyzer: Send us chemistry patents or claims. Our AI and chemists turn them into structured data: what each composition must contain, what is optional, and the ranges and properties claimed.

## Connected Vehicles study

M-Son IP's Connected Vehicles study is a global patent and product landscape of internet-connected vehicles built by subject-matter experts: 300,000+ filings collected, 260,000+ search hits reviewed, 118,434 relevant patent families (published to April 2023), 33,260 families analysed claim by claim on a 2,000+ parameter taxonomy (application, technique, communication mode, device, connectivity, vehicle type), and 1,475 products of 97 companies classified on the same taxonomy. Assignments, US litigation (734 cases) and office actions are integrated. The study was generated manually by subject-matter experts and all non-Chinese patents are updated to 2023. A free interactive dashboard shows part of the 14,005-family reporting dataset (real data, deliberately incomplete statistics), and separate reports exist for 100+ patent owners, with free 2-page previews. Any report can be refreshed to the latest data in days with M-Son IP's AI + Expert workflow.

- Study and free dashboard: https://www.mson-ip.com/#cv
- Patent-owner reports: Samsung (363 families); General Motors (321 families); Hyundai Motor Group (287 families); Ford (227 families); Toyota (219 families); Hitachi Group (204 families); Denso (189 families); Panasonic (151 families); Volkswagen Group (Porsche SE) (143 families); Continental (137 families); Bosch (132 families); Mitsubishi (126 families); Alps Group (106 families); LG (106 families); NEC (105 families); Honda (94 families); State Grid (State Council) (83 families); IBM (78 families); BMW (74 families); Chery Automobile (71 families); Daimler (69 families); BAIC Group (68 families); KT Corp (66 families); Nissan (60 families); Siemens (58 families); AT&T (57 families); SK Group (56 families); Xiamen Yaxon Networks (52 families); Sony (51 families); Chang'an University (49 families); Intel (45 families); Alphabet (Google) (44 families); Nokia (43 families); Aisin (42 families); Motorola Solutions (42 families); Ericsson (40 families); Verizon (40 families); Microsoft (37 families); ZTE (36 families); BYD (35 families); Guangdong eCar Telematics (34 families); Mazda (34 families); Pioneer (34 families); Qihoo 360 (34 families); Toshiba (33 families); Sumitomo (32 families); Tongji University (32 families); Huawei (28 families); JVC Kenwood (27 families); Xiaomi (27 families); Yazaki (27 families); Baidu (26 families); Navitime Japan (25 families); China Mobile (23 families); AB Volvo (22 families); Jilin University (22 families); Jiangsu University (21 families); Beihang University (20 families); NavInfo (20 families); Tsinghua University (20 families); Renault (19 families); Shandong University (19 families); Visteon (19 families); Tata Motors (Jaguar Land Rover) (18 families); Southeast University (17 families); Tencent (17 families); Deutsche Telekom (16 families); Nanjing University (16 families); Stellantis (PSA) (16 families); Allstate (15 families); SoftBank (15 families); Honeywell (14 families); SAIC Motor (14 families); Lear (12 families); Apple (11 families); Snap-on (11 families); Cisco (8 families); Guilin Univ. of Electronic Tech. (8 families); GAC Group (7 families); Inventec (7 families); Weichai Power (7 families); FAW Group (6 families); Valeo (6 families); BlackBerry (5 families); Chongqing University (5 families); Dongfeng Motor (5 families); RIOH (Highway Ministry of Transport) (5 families); Xiamen University (5 families); Bridgestone (4 families); Tianjin University (4 families); Xidian University (4 families); Bizmodeline (3 families); Jiangling Motors (3 families); Lenovo (3 families); Shanghai University (3 families); Great Wall Motor (2 families); BBK Electronics (1 families); CH Auto Technology (1 families); Hunan University (1 families); Knorr-Bremse (1 families); Korea Electric Power (1 families); Mastercard (1 families); ZF Friedrichshafen (1 families); Zhengzhou University (1 families); Alibaba Group; Amazon; Ant Group; Apollo Zhilian (Baidu); Bank of China; Beijing Mobike; CASCO Signal; China Railway Construction; Xpeng Motors; Hanteng Automobile; IUCF-HYU (Hanyang Univ.); ETRI; Micron; Nantong University; Noodoe; Schaeffler; Veniam; Hozon (Neta Auto)

## Reports

- Connected vehicles: global patent and product landscape: Expert-built global landscape: 118,434 relevant families, 33,260 analysed, 1,475 products, litigation and assignments.
- Connected vehicles: 100+ patent-owner reports: One report per patent owner: carmakers, suppliers, tech and telecom companies, insurers and universities. Free 2-page previews.
- Connected vehicles: free interactive dashboard: Filter 14,005 expert-classified families by application, country, legal status and year.
- Top 200 GenAI startups and 60 incumbents: Patents, funding, applications and product mapping for 200 GenAI startups, benchmarked against 60 incumbents.
- Oral delivery of proteins and peptides: patent and product landscape: 930 patent families read claim by claim, 450+ applicants, litigation, PTAB cases and assignments. With a live dashboard.
- UV LEDs by epitaxial growth of III-V semiconductors: patent landscape: 540 relevant patents analysed on problem, UV band, application, substrate and layer structure. Inventor, competitor and white-space reports. With a live dashboard.
- Tire industry: patent landscapes and technical studies: A 30,000-patent industry landscape, 1,000+ noise-reduction patents decoded, tread design analysis and problem-solution studies.
- Selective laser sintering and melting (SLS / SLM): patent landscape: 863 metal additive-manufacturing patents: owners, filing trends, countries, legal status and technology domains.
- Invalidity search: electronics demo: Prior art against a web-updated database patent (US6529908), with visual and textual claim mapping.
- Invalidity search: mechanical demo: Prior art against a Canon process-cartridge coupling patent (US8280278).
- Invalidity search: medical device demo: Seven references against a surgical cutting-accessory patent, two mapped in depth.
- Invalidity search: chemistry and pharma demo: Prior art against a rapid-onset doxylamine and pyridoxine formulation patent (US6340695).
- Invalidity study: US7296062 (browser page history): A full sample report: 12 references mapped against every claim element of a patent asserted by Retrospection Marketing LLC.
- Patentability search: chemistry demo: Is it novel to add MgO to compression-moulded foam for better thermal conductivity and cycle time?
- Patentability search: electronics sample report: A product registration system searched against five references, with benefits for users and manufacturers.
- Product-to-patent mapping: insulin delivery devices: Which devices are on the market or coming in 3 to 5 years, which patents cover them, and who owns them.
- Portfolio evaluation and optimization: a Logitech case study: 710 patent families sorted by product line; 210 mouse-related patents checked against products to decide maintain, license or abandon.
- Patent licensing study: finding licensees for a vehicle anti-theft patent: Market size, competitor patents, products, assignments, lawsuits and citations combined to find who might license.
- Global patent protection strategy: where to file: Competitors' filing, products, assignments and citations combined to decide which countries to file a vehicle anti-theft invention in.
- State-of-the-art search: UV LEDs with AlInGaN active regions: Patents and products establishing the state of the art, organized by problem, cause, solution and LED structure.
- Problem-solution analysis: tire noise and more: 1,000+ tire noise inventions broken into where, what and why the problem arises, and where and how it is solved.
- From invention to market: a four-step study for universities: Problem-solution analysis, novelty, market viability and global protection, run one after another.

## Core team

- Mohammed Mujahid, Founder: 20 years in patent search and analysis. Bachelor's in Electronics and Communication Engineering. Mohammed founded M-Son IP in 2009 and leads its patent research across the full IP lifecycle, from concept and protection to strategy, monetization and defense. He writes regularly on patent strategy, AI in patent searching and GenAI patent risk.
- Abdul Malik, Co-founder, Managing Director and Senior Patent Analyst: 15 years in patent search and analysis. Master's in HVAC (Mechanical Engineering). Abdul leads M-Son IP's work in materials, chemistry, life sciences and mechanical technologies, and manages client delivery across both offices.
- Abdul Moid, Co-founder, Operations Manager and Senior Patent Analyst: 13 years in patent search and analysis. Master's in Embedded Systems (Electronics and Communication Engineering). Abdul runs day-to-day operations and leads searches and claim charting in electronics, telecom and software, with additional work across materials and consumer products.

## Mentor

- Dr. Khaled El-Maleh, Former Senior Director of Technology, IP Department, Qualcomm. Khaled joined Qualcomm in 2000 as a senior engineer in multimedia technology and went on to serve as Senior Director of Technology in Qualcomm's IP Department, where he led IP portfolio and strategy teams for sensors and multimedia. As our mentor, he brings an inside view of how a leading technology licensor builds, values and uses patent portfolios. 200+ US and international patents as inventor; PhD and M.Eng., Electrical and Computer Engineering, McGill University; Multimedia, sensors, computer vision and IP strategy.

## Domain experience

- Electronics, telecom and software: Wireless communications (4G/LTE, 5G, Wi-Fi, MIMO and MU-MIMO, beamforming, adaptive precoding, OFDM, RF signal processing, cellular scheduling, wireless charging); Wire-based communications and networking (Telecom switching, call control, network software updates, network virtualization, software-defined infrastructure, network topology prediction); Cloud, computing and AI (Cloud computing, containers, virtual machines, remote desktop, blockchain, AI/ML, predictive analytics, algorithm optimization, formal verification); Servers, storage and memory (Nano-electronic and magnetic memory, memory arrays, remote memory access, memory-cell structures); Media and content (Video streaming, content prefetching, content delivery networks, recommendation systems, social media analytics, digital fingerprinting); Security and authentication (Malware detection, threat intelligence, digital identity verification, container and software security, network forensics); Imaging and computer vision (Object detection, visual feature matching, augmented reality, license plate recognition, digital image fingerprinting); Autonomous vehicles and ADAS (Lane departure warning, collision avoidance, automatic emergency braking, road sign recognition, driver monitoring, connected vehicles); Location-based services (Vehicle tracking, parking management, route alerts, road condition monitoring, freight arrival prediction); Semiconductors (Nanoelectronics, nanoscale magnetic structures, semiconductor memory, process and fabrication); Other digital fields (UI/UX and digital displays, record and document management, e-learning, insurance technology, quantum photonics)
- Materials, chemistry and life sciences: Polymer science and advanced materials (Water-soluble and bio-based films (PVA/PVOH), crosslinked and multilayer foams, membranes, functional coatings, adhesives, composites, flame-retardant and antimicrobial materials); Batteries and energy storage (Solid-state lithium, lithium-ion and lead-acid batteries, separators, EV conversion, smart charging); Food science and nutrition (Milk proteins, human milk oligosaccharides, microbial protein fermentation, probiotics, plant-oil fractionation, flavor compounds, food preservation, high-protein baked goods); Biotechnology and microbiology (Probiotic strains and formulations, microbial fermentation, oligonucleotides, immune-response applications, fungal biodegradation, organ-on-chip systems); Pharmaceuticals and drug delivery (Lyophilized formulations, freeze-dried drug reconstitution, drug stability, ultrasound contrast agents, nutraceuticals); Medical devices (Orthopaedic braces and splints, intravascular lithotripsy catheters, implant-related materials, medical product comparisons); Chemical engineering and processes (Gasification, hydrocarbon property prediction, fluid separation, forward osmosis, industrial filtration, colorants, glass viscosity)
- Mechanical, manufacturing and consumer products: Mechanical engineering and industrial equipment (Pipe thrusting and borehole equipment, fasteners and spring washers, piston mechanisms, cleaning equipment, robotics, blowers, truss bracing, tire structures); Manufacturing and fabrication (Precision laser cutting and lamination, polymer film production, coating processes, granulation, component fabrication); Construction and building materials (Roofing membranes, pressure-sensitive and two-part adhesives, structural truss systems, polymer foams); Consumer products, packaging and hygiene (Absorbent wipes and napkins, baby bottles, container closures, water dispensers, wearable fasteners, household cleaning tools, sanitary products); Automotive and transportation (Tire tread and casing design, motorcycle covers, combustion-to-electric vehicle conversion, automotive components); Environment and sustainability (Bio-based polymers, waste disposal systems, membrane water treatment, low-impact manufacturing); Measurement, sensing and data analytics (Seismic sensing, liquid-level signal correction, machine-learning property modeling, computer-assisted material characterization)

## Articles

- [What Is a Patent Really Worth? The Answer Depends on Who Is Asking](https://www.mson-ip.com/#post--what-is-a-patent-really-worth) (2026-09-21): A statistical score, a dollar figure or a claim chart each shows one side of a patent. Its real value depends on the stakeholder, the purpose, the market and the timing. Here is a multi-dimensional framework for valuing it.
- [OpenAI vs. Many Worlds: The Patent-Risk Blind Spot Hidden in the GenAI Stack](https://www.mson-ip.com/#post--openai-vs-many-worlds-patent-risk-blind-spot) (2026-09-04): Why continuous monitoring can still fail when patent searches are trapped by modern terminology and broad classifications.
- [Nielsen v. TVision: Why the “Problem” You Search May Be Just as Important as the Claim Features](https://www.mson-ip.com/#post--nielsen-v-tvision-search-the-problem) (2026-08-22): The Federal Circuit's Nielsen v. TVision decision shows why prior-art searches should define the technical problem at several levels, and why AI semantic search can keep a search too close to the invention's own field.
- [Can One AI Prompt Reproduce WIPO’s Generative AI Patent Landscape?](https://www.mson-ip.com/#post--can-one-ai-prompt-reproduce-wipo-genai-landscape) (2026-08-07): What WIPO’s Generative AI Patent Landscape tells us about AI-based patent searching, and why reliable landscapes still depend on disciplined search design.
- [Patent ignorance is not a risk-management strategy](https://www.mson-ip.com/#post--patent-ignorance-is-not-a-risk-strategy) (2026-08-06): The patent you ignore today may become the product crisis you face tomorrow. How to manage patent risk through a legally controlled and commercially useful monitoring process.
- [Why Two Companies Can Run the Same Patent Landscape and Walk Away With Opposite Conclusions](https://www.mson-ip.com/#post--same-patent-landscape-opposite-conclusions) (2026-07-30): Give five analysts the same 3,000-family dataset and you get five different reports. The facts are shared; the intelligence depends on the decision the landscape is built to support.
- [GenAI Patents Just Doubled In a Year & Changed the Rules on Litigation Risk: 5 Things IP Teams Must Do to Keep Your FTO Strategy From Falling Behind](https://www.mson-ip.com/#post--genai-patents-doubled-fto-strategy) (2026-07-29): New WIPO and IFI CLAIMS data show GenAI patent families nearly doubling in a year, with LLMs and agentic AI reshaping litigation risk. Five changes IP teams should make to keep FTO current.
- [GenAI scouting is broken: why incumbents need patent + product maps](https://www.mson-ip.com/#post--genai-scouting-patent-product-maps) (2026-02-25): Demos look alike and features converge. Mapping patents to products, architecture and applications shows which GenAI startups to partner with, license from or acquire.
- [The GenAI market is moving from “who builds” to “who can defend”](https://www.mson-ip.com/#post--genai-market-who-can-defend) (2026-02-20): It is no longer hard to ship impressive GenAI. Defensibility is the variable that decides outcomes, and patents plus product mapping, benchmarked across 200 startups and 60 incumbents, reveal it.
- [From Mobile Patent Wars to Generative AI Patent Litigation](https://www.mson-ip.com/#post--mobile-patent-wars-to-genai-litigation) (2026-01-06): Why early, focused IP intelligence matters in generative and agentic AI, and what the smartphone patent wars teach us about the litigation to come.
- [Connected Vehicles: Why We Read 33,260 Patents Instead of Counting Them](https://www.mson-ip.com/#post--connected-vehicles-study-launch) (2026-01-14): Keyword and classification searches either miss connected-vehicle patents or bury them in noise. Here is how our experts built a landscape that buyers can act on.
- [China Files Most Connected-Vehicle Patents. Reach Is Another Story.](https://www.mson-ip.com/#post--china-connected-vehicle-patents-volume-vs-reach) (2026-02-11): China's share of first filings rose from 5% to 64% in a decade. But family size, utility models and citations show why volume alone misleads.
- [Who Litigates Connected-Vehicle Patents? Mostly Not the Carmakers](https://www.mson-ip.com/#post--connected-vehicle-litigation-who-asserts) (2026-03-12): 734 US litigation and post-grant cases involve patents in our study. The most active owners are licensing companies and individual inventors.
- [1,002 Connected-Vehicle Patent Families Changed Hands. Here Is Who Bought Them.](https://www.mson-ip.com/#post--connected-vehicle-patent-consolidation) (2026-04-15): Acquisitions moved about 7% of the reporting dataset to a new parent group. Portfolio counts that ignore this miss who really holds the rights.
- [What Carmakers Patent vs What They Sell in Connected Vehicles](https://www.mson-ip.com/#post--connected-vehicle-patents-vs-products) (2026-05-13): Patents cluster around vehicle infrastructure and location tracking. Products lead with safety and autonomy. The gap is where opportunities hide.
- [Cyber Security in Connected Vehicles: Patents Grew Fivefold in Ten Years](https://www.mson-ip.com/#post--connected-vehicle-cyber-security-patents) (2026-06-10): Vehicle cyber-security filings rose from about 20 a year to more than 100. Individual inventors hold more of these families than any company.
- [1,103 Connected-Vehicle Patent Families Belong to Universities and Research Institutes](https://www.mson-ip.com/#post--universities-connected-vehicle-patents) (2026-07-15): Research institutes hold about 8% of the reporting dataset, led by Chinese universities. That is a licensing and partnership pool few companies look at.
- [Location Tracking Is the Backbone of Connected-Vehicle Patents](https://www.mson-ip.com/#post--location-tracking-backbone-connected-vehicles) (2026-08-12): More than a quarter of families rely on location tracking, and GPS is the most cited device. V2X communication dominates how vehicles talk.
- [Battery and Charging: Where Energy Companies Meet Carmakers](https://www.mson-ip.com/#post--ev-charging-connected-vehicle-patents) (2026-09-16): 569 families cover connected battery and charging. China's State Grid holds more of them than any carmaker.
- [Refreshing an Expert-Built Landscape With AI + Expert](https://www.mson-ip.com/#post--connected-vehicles-study-update-ai-expert) (2026-10-21): Our connected-vehicle study was built by experts. Now we use that expert base to train AI and bring any report up to date in days.
- [Before the Deal: What Our 2019 Oral Peptide Landscape Showed](https://www.mson-ip.com/#post--oral-peptide-delivery-patents-before-the-deal) (2026-01-28): In 2019 our experts read 930 oral peptide delivery patent families. The most active company owner was Emisphere. A year later Novo Nordisk paid $1.8 billion for it.
- [Why We Read Claims: From Search Hits to Relevant Patents](https://www.mson-ip.com/#post--why-we-read-claims-not-keywords) (2026-02-25): 35,000 screened to 930 relevant. 3,179 reviewed to 540 relevant. Our landscapes keep a small share of the hits, and that is the point.
- [UV LEDs: What 540 Patents Say About the Problems Engineers Are Solving](https://www.mson-ip.com/#post--uv-led-patents-problems-still-unsolved) (2026-03-25): Poor quantum efficiency, threading dislocations and light absorption top the list. Our expert-built UV LED dataset shows where the problems sit and who is solving them.
- [Which Patents Earn Their Fees? Mapping a Portfolio to Products](https://www.mson-ip.com/#post--portfolio-optimization-mapping-patents-to-products) (2026-04-28): Using Logitech's 710 public patent families as a case study, we show how mapping patents to products splits a portfolio into maintain, license and abandon.
- [Tire Noise: What 1,000 Patents Say Actually Reduces It](https://www.mson-ip.com/#post--tire-noise-patents-problem-solution) (2026-05-27): We broke 1,000+ tire noise inventions into where the noise comes from and how it is solved. Groove design dominates.
- [How We Run an Invalidity Search: Four Demos, Four Technologies](https://www.mson-ip.com/#post--how-we-run-an-invalidity-search) (2026-06-24): Electronics, mechanical, medical device and pharma: the same process, adapted to where each field hides its prior art.
- [Start with the Products: Mapping Insulin Delivery Devices to Patents](https://www.mson-ip.com/#post--product-to-patent-mapping-insulin-devices) (2026-07-29): Pens, pumps, patches and oral forms: how we found devices on the market and in development, then mapped them claim by claim to the patents behind them.
- [Finding a Licensee for a Single Patent: Six Methods That Work](https://www.mson-ip.com/#post--finding-a-licensee-for-one-patent) (2026-08-26): Market size, competitor patents, products, assignments, lawsuits and citations: each points to different potential licensees.
- [Metal 3D Printing Patents: Who Owns Laser Sintering and Melting](https://www.mson-ip.com/#post--metal-3d-printing-patents-laser-sintering-melting) (2026-09-29): 863 patent records on selective laser sintering and melting: 3D Systems, GE and EOS lead, and chemistry patents edge out mechanical ones.
- [For Universities: Four Questions Before Filing an Invention](https://www.mson-ip.com/#post--four-questions-before-filing-an-invention) (2026-10-14): Problem, novelty, market and geography. The four-step study we run with tech-transfer offices before they spend on filing.

## Notes

- M-Son IP provides search and analysis, not legal advice.
- Full article text: llms-full.txt