Technology
Accelerating technology companies with AI
Enabling software and product companies to drive more value, improve processes and spearhead breakthroughs with AI
Your growth partner in AI in Technology
Technological development is dynamic and fast-paced, and swift adaptation is key. Today’s users demand agility and personalization and businesses must evolve with these changing trends and expectations. Fusemachines offers over a decade of expertise in delivering AI-powered speed and customization to the industry. Collaborating with businesses at every stage of their AI journey, we provide tailored AI products and solutions to help IT companies tackle these challenges head on.
Here’s why you should partner with us
10+ years of consistently delivering exceptional AI Solutions and Services in the technology.
Expert understanding of business challenges and evolving technology landscape
At the forefront of AI-assisted and innovative data engineering and application development
Our areas of expertise in technology
Artificial Intelligence
Leverage our advanced AI solutions to streamline operations, improve efficiency, and unlock opportunities
Software Development
Use our custom software development services to unlock the potential of your IT enterprise. From design to deployment, our expert team provides tailored solutions to meet your unique needs.
Cloud Computing
Utilize our cloud computing solutions for IT companies to achieve your business goals faster and more efficiently at reduced costs and increased flexibility.
Data Engineering
Use our industry-leading data engineering solutions including CMS, web scraping, data warehousing, NLP and data visualization tools to transform your IT business.
IT Consulting
Leverage our IT consulting services to better understand your goals and audience, conduct audits, develop successful strategies, and bring your business to the next level.
Design and Product Management
Leverage our design and product management services including UX/UI, product strategy, project management, and quality assurance to build top-quality products.
Mobile App Development
Unlock the potential of mobile technology with our comprehensive mobile app development solutions. Our team is committed to delivering high-quality, cross-platform & innovative apps tailored to your unique IT requirements.
Want more information?
Book a complimentary consultation with an AI expert today.
Our AI engines expedite retail & consumer goods business value with industry-specific solutions
Xtract AI EngineTM
The future of Generative AI for Information Extraction
Answer GenTM
A GenAI based Answer Generation Engine from Documents
Fraud Detection AI EngineTM
Accelerate how you identify emerging fraud patterns and investigate them with AI
Forecast AI EngineTM
Advanced AI for Demand & Inventory Forecasting
Our technology case studies
Dive into our case studies, showcasing the powerful impact of innovative AI products and solutions in revolutionizing technology sector.
AI information extraction engine for downstream analytics
Fusemachines helped a leading technology company which provides a robust accounts payable platform with AI information extraction engine for downstream analytics.
Problem Statement
- Extracting key-values from a wide variety of vendor-specific financial documents.
- Adapting to the ever expanding list of possible document types (templates) per vendor.
- Achieving near perfect accuracy in extracting the relevant information.
Solution
- Fusemachines implemented a Rule-Based Key-Value Extraction technique to parse relevant information from documents.
- It identified areas of interest using keys and proximity coordinates, extracted key-values from line-items, and sanitized the data before converting it to JSON.
- This process, built on a REST API, processed client PDFs asynchronously, returning the final JSON file upon completion of each document's processing.
Results
- Improved Efficiency and productivity as a result of accurate extraction.
- Accurate Key value extraction for downstream analytics and visualization.
- Bettered Financial expense analytics and intelligence.
Detect malicious sessions in real-time
Fusemachines helped a leading cybersecurity company build AI models to detect malicious sessions in real-time.
Problem Statement
- Detect the malicious sessions present in the network in real-time.
- Noisy data (public malware contained both malicious and non-malicious sessions, label noise).
- Attacks evolved and changed their fingerprint, and the system needed to be continuously updated.
Solution
- Real network traffic data, captured in pcap files, trained anomaly detection models to differentiate between benign and malicious sessions.
- The project had two approaches: feeding raw internet data directly into the model, and using 144 hand-engineered features.
- Two architectures, AutoEncoder and DevNet, were implemented. AutoEncoder trained solely on benign data, while DevNet also included malicious sessions, both aiming to build a benign profile for anomaly detection.
Results
- Detected 4K malicious public IPs and 407K malicious sessions.
- Accurate Detection of malicious IPs and sessions.
- 0.97 AUC Score in our dataset with Devnet Model.
Fusemachines helped a leading technology company which provides a robust accounts payable platform with AI information extraction engine for downstream analytics.
Problem Statement
- Extracting key-values from a wide variety of vendor-specific financial documents.
- Adapting to the ever expanding list of possible document types (templates) per vendor.
- Achieving near perfect accuracy in extracting the relevant information.
Solution
- Fusemachines implemented a Rule-Based Key-Value Extraction technique to parse relevant information from documents.
- It identified areas of interest using keys and proximity coordinates, extracted key-values from line-items, and sanitized the data before converting it to JSON.
- This process, built on a REST API, processed client PDFs asynchronously, returning the final JSON file upon completion of each document's processing.
Results
- Improved Efficiency and productivity as a result of accurate extraction.
- Accurate Key value extraction for downstream analytics and visualization.
- Bettered Financial expense analytics and intelligence.
Fusemachines helped a leading cybersecurity company build AI models to detect malicious sessions in real-time.
Problem Statement
- Detect the malicious sessions present in the network in real-time.
- Noisy data (public malware contained both malicious and non-malicious sessions, label noise).
- Attacks evolved and changed their fingerprint, and the system needed to be continuously updated.
Solution
- Real network traffic data, captured in pcap files, trained anomaly detection models to differentiate between benign and malicious sessions.
- The project had two approaches: feeding raw internet data directly into the model, and using 144 hand-engineered features.
- Two architectures, AutoEncoder and DevNet, were implemented. AutoEncoder trained solely on benign data, while DevNet also included malicious sessions, both aiming to build a benign profile for anomaly detection.
Results
- Detected 4K malicious public IPs and 407K malicious sessions.
- Accurate Detection of malicious IPs and sessions.
- 0.97 AUCScore in our dataset with Devnet Model.
"Fuse’s ability to deliver consistently outstanding solutions and strategic counsel is on par with their commitment to nurturing AI and tech talent through global education initiatives. Their unique role as experts and educators motivates us to continue finding ways to work together."
Bharat Krish
President, TIME Digital and CTO
FAQs
Customized generative AI models are becoming increasingly important as they cater to specific market and user needs. These tailored models are more efficient, offer enhanced privacy and security, and are better suited for specialized domains compared to large, general-purpose models.
The technology sector is witnessing a growing need for AI and machine learning talent, especially professionals who can bridge theory and practice. Skills in AI programming, data analysis, and MLOps are crucial for deploying, monitoring, and maintaining AI systems in real-world settings.
Shadow AI refers to the use of AI tools within an organization without explicit approval or oversight from the IT department. While it demonstrates a proactive approach to technology, it poses risks related to security, data privacy, and compliance.
Generative video models are being used increasingly in the film and marketing industries for tasks like lip-syncing actors’ performances and creating special effects. They are also raising concerns about the future role of actors and potential misuse in the industry.
The proliferation of AI-generated election disinformation is a growing concern. The ease of creating deepfakes and AI-generated content is likely to influence political climates and challenge the ability to discern real from fake content online.
Inspired by generative AI techniques, there's a trend toward developing general-purpose robots capable of performing a wide range of tasks. This shift from specialized to multipurpose robots marks a significant evolution in robotics.
Generative AI is transforming how businesses interact with data, shifting from a search-based model to an advisory model. This involves using AI chatbots that can synthesize information, provide answers and advice, and serve as LLM-advisors for data-driven decision-making.
Solid and contextual data foundations are essential for effective AI implementation. Technologies like knowledge graphs, data mesh, and data fabric are crucial for organizing information and supporting AI-driven knowledge management.
Businesses are increasingly fine-tuning language models for specific use cases. Options include training own LLMs, adapting existing ones for domain-specific tasks, and using smaller language models for specialized applications.
Diversity in AI initiatives is vital to address biases in training data and ensure inclusive outcomes. Diverse technical teams are essential for challenging results and ensuring AI models are ethical and representative.
