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Austin, United States
1-10 Employees
2016
Ascend is a performance digital marketing agency located in Austin, TX. Receive important updates, news and exclusive offers related to Ascend.
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Ascend: Digital Marketing Agency / AI, Machine Learning & Predictive Analytics
... A new breed digital marketing agency that delivers profitable outcomes through AI, Machine Learning & Predictive Analytics. ...
Saint Petersburg, United States
1-10 Employees
2020
Store your data in the most useful way possible. Create customized dashboards and alerts based on your needs and use cases. See how you match up with industry benchmarks. Create insights from the data that is gathered. Use AI and ML to build predictive analytics.
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AI Predictive Analytics and BI
... And since the Dados data engine can join … AI Predictive Analytics and BI Read More » ...
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We Make Sense out of Data | Predictive Analytics Lab
... We Make Sense out of Data | Predictive Analytics ...
United States
51-100 Employees
2014
At Guidewire, we are utterly committed to your success. Experience our story from Guidewire professionals all over the world. Guidewire celebrates the recognition by Gartner in its 2021 Gartner Magic Quadrant for P&C Core Insurance Platforms, North America. Gartner has recognized Guidewire Software as a Leader in the 2021 Magic Quadrant for Non-Life Insurance Platforms, Europe, for the fourth consecutive year. Guidewire has been positioned as a Leader by independent research firm in P&C Claims Management Systems evaluation. Guidewire experts reveal how insurers will strengthen the industry with evolving innovations. Guidewire named AWS 2023 Global Partner of the Year - Financial Services. Guidewire wins all three Celent XCelent awards and named a Luminary in North America policy administration report.
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Predictive Analytics Software für Versicherungen | Guidewire
... Guidewire Predictive Analytics für Versicherungen: ✓datenbasierte Entscheidungen treffen ✓Kosten senken » Datenanalyse-Software entdecken! ...
Vancouver, Canada
11-50 Employees
Our services enable healthcare providers to identify individuals at risk for specific conditions and develop personalized treatment plans, improving health outcomes and reducing healthcare costs. Our Solution provides Predictive and Preventive Health Analytics to providers around the globe. Extra Health Biotech is a cutting-edge AIcompany specializing in predicting human health in special areas. We use state-of-the-art algorithms and machine learning techniques to analyze complex health data and provide accurate (up 95% accuracy) predictions of future health outcomes. At Extra Health Biotech, we are committed to revolutionizing healthcare by providing advanced predictive analytics solutions that enhance quality of life for individuals and populations alike. Provides predictive analysis for patients, identifying health risks and anticipating future events to help healthcare providers create effective treatment plans and improve health outcomes. Provide you with insight information about your patient's treatment and health improvement by using our mobile app, Artificial Intelegent and Machine Learning solutions. We do many R&D yearly for our customers to provide customer solutions tailored to their needs.
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with predictive analytics
... Extra Health Biotech – Predictive Health Analytics ...
McLean, United States
11-50 Employees
2018
MFGS, Inc. is the trusted advisor to the U.S. Government, its partners, and system integrators for achieving optimal efficiency throughout an agency’s enterprise software architecture. We bring a comprehensive portfolio of enterprise-grade software capabilities and a deep understanding of how DOD agencies operate to support your entire software development lifecycle, enabling you to securely plan, build, deliver, and run agency missions.
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Predictive Analytics
... Predictive Analytics | MFGS, Inc. ...
Tel Aviv-Yafo, Israel
11-50 Employees
2016
Founded in 2018, Pecan is a predictive analytics platform that leverages its pioneering Predictive GenAI to remove barriers to AI adoption, making predictive modeling accessible to all data and business teams. With Pecan’s fusion of predictive and generative AI, realizing the business impact of AI is now far faster and easier. Pecan AI’s new tool, Predictive GenAI, combines some of the power of modern generative AI capabilities with predictive machine learning. The new feature combines Pecan’s AI-powered models for business predictions with the generative AI features found in models such as ChatGPT. SVP of Product Limor brings two decades of software development and management experience to Pecan. VP of Finance Riki is a seasoned finance executive passionate about scaling early-stage startups to mature businesses. Riki is a Certified Public Accountant and holds a BBA from Ruppin Academic Center. VP of R&D Tomer is a veteran engineering leader, with strong technical, organizational and customer-facing skills, and extensive background in both software engineering and product management.
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Predictive Analytics for Customer Churn
... Predict 85% of customer churn with AI-powered predictive analytics. ...
Brisbane City, Australia
11-50 Employees
2018
We are here to help organisations implement impactful and effective solutions using emerging technologies without being caught up in the hype. We are on a mission to improve organisations and humanity with every project we undertake. We implement these solutions & support them post delivery. We believe that, not all emerging technologies are useful but the right ones are instruments of great positive change. We believe that good solutions have a tangible, positive impact on people. Our software solutions provide organisations with measurable time and cost savings. Efficient and optimised edge computing to provide next-gen capabilities to all micro and macro edges of your device fleet using image recognition, process automation and IoT mesh optimisation. Our IoT fleet optimisation solutions will help you deliver more value to your outdoor workers.
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Business Intelligence & Predictive Analytics Solution
... Business Intelligence & Predictive Analytics ...
Villeneuve-d'Ascq, France
1-10 Employees
Our team is composed of leading professionals and academic with more than 75 years of experience in:.
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Predictive Analytics
... Predictive Analytics ...
Rolle, Switzerland
11-50 Employees
2014
We are the only company to provide auto-Machine Learning technology fully dedicated to time-series. Predictive Layer provides a robust decisioning platform to support products and services demand based on our innovative time series algorithms. Created in 2015 and headquartered in Switzerland, we rely on an international team of experts with a strong background in Mathematics, AI and Data Science, who regularly collaborate with some of the best research laboratories in the world. Thanks to our AI technology dedicated to time series forecasting, with unique explainability capabilities, we are the expert of supply/demand and price forecasting for many industries. We offer a strong international team of AI and Machine Learning experts, reinforced by continuous investment with renowned research labs. We operate live models for more than 6 years and develop a strong experience to customize models or strategies for our customers. We’ve operated live models for over 7 years and developed strong expertise in customizing models and strategies for our customers. Predictive Layer’s AI-powered solutions are revolutionizing the energy and commodities markets, delivering unparalleled insights for smarter decision-making and optimized operations.
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Revolutionizing Finance with AI-Driven Predictive Analytics
... Revolutionizing Finance with AI-Driven Predictive Analytics – Predictive ...
Technologies which have been searched by others and may be interesting for you:
Some interesting numbers and facts about the results you have just received for Predictive Analytics
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 1651 |
| Amount of suitable service providers | 1423 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 2014 |
| Youngest suiting company | 2020 |
Predictive analytics is a branch of advanced analytics that utilizes current and historical data to forecast activity, behavior, and trends. It involves the use of statistical algorithms, machine learning techniques, and data mining to analyze facts and make predictions about future or otherwise unknown events. At its core, predictive analytics processes vast amounts of data through mathematical models to predict outcomes with a significant degree of accuracy. This methodology is increasingly pivotal across various sectors, including finance, healthcare, marketing, retail, and more, enabling organizations to make informed decisions by anticipating trends and behaviors. The role of predictive analytics in these fields is transformative, offering insights that lead to optimized operations, enhanced customer experiences, and improved risk management. By accurately forecasting future trends and behaviors, businesses can strategize proactively, align resources more effectively, and mitigate potential risks before they materialize. The impact of predictive analytics extends beyond mere operational enhancements to foster innovation, drive revenue growth, and build competitive advantage in the rapidly evolving digital landscape. Through the strategic application of predictive analytics, organizations are not only able to navigate the complexities of their respective industries but also set new benchmarks for efficiency and success.
1. Improved Decision Making
Predictive analytics empowers organizations with data-driven insights, enabling them to make more informed decisions. By analyzing past and current data, businesses can anticipate outcomes and trends, leading to strategies that are more aligned with future market movements.
2. Enhanced Efficiency
This approach streamlines operations by identifying which areas require improvements or adjustments, reducing wasted resources and time. It allows companies to focus their efforts on strategies and processes that are most likely to yield positive results, thereby increasing overall efficiency.
3. Risk Reduction
Predictive analytics plays a critical role in identifying potential risks and vulnerabilities within a business operation. By foreseeing possible issues, companies can devise preemptive measures to mitigate risks, safeguarding against future uncertainties and potential losses.
4. Customized Customer Experiences
Leveraging predictive analytics enables businesses to tailor their services or products to meet the specific needs and preferences of their customers. This personalization enhances customer satisfaction and loyalty, which is pivotal for long-term business success.
While evaluating the different suppliers make sure to check the following criteria:
1. Technological Compatibility
Ensure the supplier's technology can seamlessly integrate with your existing systems and data infrastructure without significant overhauls.
2. Scalability
The solution should be scalable to accommodate future growth in data volume and complexity, supporting your evolving predictive analytics needs.
3. Data Security Measures
Evaluate the supplier's commitment to data security, including compliance with relevant regulations and standards to protect sensitive information.
4. Model Accuracy and Performance
Assess the accuracy and performance of the supplier's predictive models, looking for evidence of successful real-world applications.
5. Customization Capabilities
The supplier should offer customization options that allow you to tailor the predictive analytics solutions to your specific business requirements.
6. Support and Maintenance
Consider the level of ongoing support and maintenance provided, ensuring that you have access to timely assistance and updates.
Predictive analytics revolutionizes the way businesses anticipate consumer behavior, optimize operations, and minimize risks. In the retail sector, companies leverage predictive models to forecast sales trends, enabling precise inventory management and targeted marketing campaigns. This approach not only reduces overhead costs but also enhances customer satisfaction by ensuring the availability of in-demand products. In the financial services industry, predictive analytics plays a crucial role in assessing credit risk. By analyzing historical data, financial institutions can predict the likelihood of default, thereby making informed lending decisions. This capability not only mitigates financial risk but also streamlines the loan approval process, benefiting both lenders and borrowers. Manufacturing companies use predictive analytics for predictive maintenance, predicting machinery failures before they occur. This preemptive approach minimizes downtime and extends the lifespan of equipment, significantly reducing maintenance costs and increasing operational efficiency. Healthcare providers apply predictive analytics to improve patient care through predictive diagnostics. By analyzing patient data, healthcare professionals can identify individuals at high risk of developing certain conditions, facilitating early intervention and personalized treatment plans. In the realm of supply chain management, predictive analytics enables companies to anticipate demand fluctuations and supply chain disruptions. This foresight allows businesses to adjust their strategies proactively, ensuring seamless operations and maintaining competitive advantage in a dynamic market environment.
Predictive analytics, a cornerstone of modern data science, has achieved a high Technology Readiness Level (TRL), typically positioned at TRL 8 or 9. This classification reflects its extensive validation in real-world settings and its integration into operational environments. The technical foundation of predictive analytics rests on advanced statistical, machine learning, and artificial intelligence algorithms that have matured significantly over the past decades. These techniques are capable of processing large datasets, identifying patterns, and making accurate forecasts based on historical data. The progress in computational power and the availability of big data have further propelled predictive analytics to these high TRLs. Organizations across various sectors, including finance, healthcare, and retail, now routinely employ predictive analytics for decision-making, underscoring its effectiveness and reliability. The movement towards cloud computing has also enhanced the scalability and accessibility of predictive analytics tools, allowing even small businesses to leverage this technology. Continuous advancements in algorithm efficiency and data processing methods are fine-tuning predictive analytics, ensuring its ongoing relevance and applicability in a rapidly evolving technological landscape. This culmination of technical progress and practical validation underscores why predictive analytics occupies its current esteemed position on the TRL scale.
In the Short-Term, predictive analytics is set to become more accessible to non-technical users through advancements in user-friendly interfaces and automated data cleaning processes. This democratization of technology will enable a broader range of industries to leverage predictive insights for decision-making, enhancing efficiency and precision. Integration with cloud computing will further streamline data management and analysis, making predictive tools more scalable and cost-effective. Moving into the Mid-Term, we will witness the integration of predictive analytics with artificial intelligence (AI) and machine learning (ML) technologies becoming more sophisticated. This synergy will lead to the development of self-learning predictive models that can adapt to new data in real-time, providing more accurate and dynamic forecasts. Additionally, the expansion of IoT devices will generate vast new data sources, enriching the datasets available for analysis and enabling more nuanced and sector-specific predictions. In the Long-Term, predictive analytics is expected to play a crucial role in shaping autonomous systems across various sectors, including transportation, healthcare, and urban planning. Predictive models will be capable of processing complex variables in real-time, allowing for the development of self-regulating systems that can predict and mitigate potential issues before they arise. Furthermore, the ethical and privacy considerations surrounding predictive analytics will drive the development of new standards and regulations, ensuring the responsible use of predictive technologies.
