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Innovations Lab

AIML

Alcrucis’s sophisticated AI techniques fuse artificial intelligence and business to deliver clear, measurable results.

Artificial Intelligence (AI) driven technology boom in growth is restructuring business as we know it today. While early adopters have already reaped the benefits of AI, the rest of the economy is not far behind; according to survey of lot of executives believe that organizations will actively implement AI and machine learning (ML) within the next 3 years. Moreover, companies adopting AI are set to achieve tremendous growth of companies. The widespread of artificial intelligence companies all around the world evidences this paradigm shift in the business world. Alcrucis is very excited to leverage the tremendous potential of AI for your products, solutions, and services.

Alcrucis’s sophisticated AI techniques fuse artificial intelligence and business to deliver clear, measurable results. Alcrucis is proud to follow an Agile methodology in all offerings. This coordinated, iterative approach ensures maximum collaboration among teams so that important project tasks are completed in parallel. Our team of expert engineers use the latest advances in AI to craft powerful models of verified database/warehouse data to process text (NLP), images, speech, and videos. You can be assured of better time to market and optimized cost based on our execution model.

Deep Learning

Use different neural networks such as CNN and RNN for detection and analysis of rich image, audio and video data.

Nautural Language Processing (NLP)

Apply ML to process text and speech for business use cases, for example customer sentiment analysis and marketing campaign automation.

Chatbots

Use advanced AI for human like interactions with a virtual assistant, which saves time on mundane tasks.

Big Data Architecture

Handle seamlessly the ingestion, processing and analysis of vast quantities of data.

Segmentation/Recovering insights

Divide data into cogent segments to derive actionable insights tailored for each segment.

Predictive Modelling and Anomaly Detection

Use proven ML-based techniques such as logistic regression and unsupervised learning approaches to predict trends and detect potentially threatening anomalies in data.

Time Series/Streaming Analysis

Ingest vast amounts of continuously updated data from disparate sources, including IoT-enabled products. Monitor this real-time data with sophisticated time series variable analysis to understand underlying correlations and make predictions.

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