Internal Engineering · internal
In-house
152 verified customer use cases (77% with quantified ROI · Avg Value Score 80.3 · 92% with mapped architecture components).
- Verified stories
- 152
- Quantified ROI
- 77%
- Avg value score
- 80.3
- Industries served
- 16
- Distinct products
- 472
In-house Sample Feb 12, 2025 Deutsche Telekom Conventional low-interaction honeypots are easy for attackers to recognize and abandon, while medium- and high-interaction honeypots are more resource-intensive, harder to manage, and can create greater risk because… Beelzebub · Galah · Large Language Models (LLM) In-house Sample Feb 11, 2025 Allianz United Kingdom Allianz UK underwriters had to search through as many as 70 lengthy guidance documents during underwriting, spending significant time finding the right rules and answers, which slowed response times, risked missing… 260 Property and Liability Underwriters BRIAN In-house Sample Feb 7, 2025 Allianz Customer care agents and operational experts across Allianz entities in Germany had to navigate the AWISO knowledge library, an extensive repository of thousands of documents, making information retrieval slow and… accuracy rate exceeding 90% for common queries AWISO knowledge library · Enterprise Knowledge Assistant (EKA) · Future Cloud platform In-house Sample Feb 6, 2025 BNP Paribas Cardif BNP Paribas Cardif handles more than 20 million customer phone calls each year, but manual review was too limited and slow to extract actionable insight from conversations for service improvement, product fit checks,… At least 30 minutes of listening and analysis for a 15-minute telephone call Call Analyzer · Speech to Text artificial intelligence models · data visualization tools In-house Sample Est. · Feb 3, 2025 Merck Merck researchers need to navigate large data sets, refine hypotheses, and complete repetitive and differentiated analysis tasks more efficiently during drug discovery and development. In-house Sample Jan 16, 2025 BNP Paribas BNP Paribas Global Markets sales teams were manually interpreting client requests for quotes from chat and email and filling response forms on a dedicated platform, which took several minutes per quote and made speed… around 50,000 requests across several asset classes every month BERT · Chat2Trade · internal pricing tools In-house Sample Jan 8, 2025 General Motors Prospective EV buyers and drivers remain concerned about finding convenient public charging, so GM needed a way to identify the most strategic new charging locations to expand network coverage and improve the charging… 2,850 DC public charging stalls In-house Sample Dec 23, 2024 Rockwell Automation Rockwell Automation wanted to add AI across the production asset life cycle so its automation products could improve design efficiency, operations, throughput, yield, quality inspection, maintenance decisions, and… The difference between a feasible and an optimal solution can be 10%. ControlLogix · Emulate3D simulation · FactoryTalk Analytics In-house Sample Dec 20, 2024 Accenture Accenture wanted customer- and employee-facing AI interactions to sound less generic, reflect the brand's voice and values, handle routine service tasks, and scale personalized support without increasing operating… cloud infrastructure · gen AI-powered conversational agents · integrated data systems In-house Sample Dec 12, 2024 Vodafone Business IoT Vodafone Business IoT needed a faster, more proactive way to detect service anomalies across its managed IoT connectivity operations so support teams could respond before issues affected customers at global scale. over 180 countries AI-powered anomaly detection tool In-house Sample Nov 26, 2024 Telefónica España Transport-network technicians were spending significant time searching lengthy, complex, multilingual manufacturers' manuals and internal documents to resolve incidents, check component characteristics, and find action… RAG (Retrieval-Augmented Generation) · language model (LLM) · technical documentation ChatBot In-house Sample Nov 20, 2024 General Motors GM must validate and debug vehicle software that affects safety, navigation, entertainment, and core vehicle operations before release, because modern vehicles contain more than 100 million lines of code and the company… more than 100 million lines of software code AI · Automated testing · custom device In-house Sample Oct 30, 2024 Walmart Holiday shoppers face stress finding relevant gifts, comparing options, checking out quickly, securing delivery slots, and resolving post-purchase issues such as returns. Roughly 12 million additional U.S. households will benefit from expanded delivery coverage this year AI-driven comparison feature · AI-driven geospatial platform · AI-powered exit technology In-house Sample Oct 25, 2024 EnBW EnBW needed to move beyond reactive, manual analysis of massive wind-turbine telemetry so it could detect faults and anomalies early across a heterogeneous fleet before they caused expensive failures or downtime. 450 wind turbines are monitored with the aid of AI In-house Sample Oct 17, 2024 OMV OMV needs to reduce uncertainty in complex geothermal and carbon capture and storage decisions, while also making large volumes of structured and unstructured subsurface data easier for geoscientists to find, summarize,… AI-driven decision-making tool · OMV Energy Chat Bot · knowledge graphs In-house Sample Oct 11, 2024 General Motors GM's race teams must interpret noisy driver radio, live telemetry, lap and track context, and trackside imagery fast enough to make pit and vehicle decisions during a race, creating more real-time data than humans can… "a second-by-second view of how the car is performing" In-house Sample Sep 23, 2024 Zurich Insurance Group Zurich needed to review very large claims volumes more efficiently, reduce investigator drudgery and false positives, and detect fraudulent claims and emerging fraud patterns quickly enough to protect honest customers… a team of 50 specialists Allegro · Zurich’s internal AI chatbot · Zurich’s proprietary fraud scoring tool In-house Sample Aug 26, 2024 ZF ZF needed to shorten development cycles, analyze large volumes of customer requirements, speed testing and validation, and estimate operating parameters that cannot be physically measured in products such as electric… AI Tech Center · Virtual Sensors · cubiX In-house Sample Aug 13, 2024 NatWest Group NatWest Group wanted colleagues to get faster, more efficient support for workplace and HR queries while reducing the load on human support teams for routine questions. Ask Archie In-house Sample Aug 2, 2024 BBVA BBVA needed to help customers manage spending, savings, investments, and future outgoings with personalized guidance, while also coping with inconsistent transaction data from other banks that was too sparse for simple… 391 million interactions with these features across all the countries where BBVA is present, 49% more than in… BBVA app · Budgets · account balance prediction model In-house Sample Jul 25, 2024 Rio Tinto Rio Tinto wanted AI and advanced analytics solutions that help operating teams work more safely and efficiently, and it needed a fast way to support its Annual Planning Review workshop with better access to… timely delivery in only 3 weeks GPT-like knowledge agent · Generative AI · Large Language Models (LLMs) In-house Sample Jul 16, 2024 BBVA BBVA needed to determine whether customers who use its financial health tools actually save more because of those tools, while removing the influence of confounding variables such as age, income, and spending level.… 11 percent more savings in Spain Apartados · BBVA Plan · BBVA app In-house Sample Jul 15, 2024 Bosch China Bosch China wanted to improve pre-sales support by connecting offline and online consumer behavior, increasing product awareness, improving customer experience, and enabling more effective cross-selling across product… impact around 6 million Bosch members and 10 million Bosch customers on the e-commerce platform and offline… Bosch Consumer Data Center · Large Language Models (LLM) · MyBoschClub 3.0 In-house Sample Jun 20, 2024 Target Store team members need fast, reliable answers to process and procedure questions, plus on-the-job coaching for new and seasonal workers, so they can handle operations efficiently and serve guests better. about 400 stores Store Companion