AI / GenAI
AI plays a pivotal role in the gamut of DIGIOTAI offerings, as it transforms an enterprise to make Humans and Machines Interoperability seamless in a Machine Economy.
Bots & Virtual Assistants
We use cognitive frameworks of Microsoft and IBM (Watson) and also using our custom built cognitive frameworks.
DIGIOTAI, works on emerging AI tech stacks and platforms like SingularityAI.Net to come up with actionable AI paradigms
AI / Gen AI Framework
At DIGIOTAI, through our team of experienced ML and NLP SMEs, we have developed an AI framework which can easily be customized and tweaked based on Industry regulations and needs.
DIGIOTAI also develops Pre-Configured Learning Models for specific technology, process or industry buckets.
NLP Modeling
As a part of AI Modeling, we look at majorly defining the Core Modules, API Engines and the Learning Models using our NLP.
Using advanced Machine Learning protocols, Digiotai ensures a seamless cognitive experience.
AI / Gen AI plays a pivotal role in the gamut of DIGIOTAI offerings, as it transforms an enterprise to make Humans and Machines Interoperability seamless in a Machine Economy. DIGIOTAI boasts of a team of Data Scientists and Data Engineers, who has been able to develop a flagship AI platform that is industry agnostic and can be implemented with a rapid turnaround time.
DIGIOTAI, works on emerging AI tech stacks and platforms like SingularityAI.Net to come up with actionable AI paradigms also enabling ‘Resilience’ criterions in a machine economy in the event of a Dark AI indulgence, powered with custom Deep Learning and decentralized Blockchain stacks.
– NLP Modeling – As a part of AI Modeling, we look at majorly defining the Core Modules, API Engines and the Learning Models using our NLP and Machine Learning protocols, ensuring a seamless cognitive experience.
– Bots & Virtual Assistants – Using cognitive frameworks of Microsoft and IBM (Watson) and also using our custom built cognitive frameworks, we are able to ensure that our AI exposure invokes a near real interactive experience. While on-boarding, we are able to classify our Bots as:
– Virtual Assistants (VAs) – Providing responses for FAQs, ensuring a site guide, and providing a live agent interaction experience.
– Intelligent Bots/VAs Paradigms Ingestion – Here we use our custom Cognitive frameworks to ensure it gives proactive prompts, able to integrate with backends and fetch relevant results, provide contextual learning based responses using predictive engines like Watson, etc.
– Onboarding Bots/VAs – Here we are able to navigate to relevant forms, and help form filling using speech to text conversions etc.
DIGIOTAI’ s AI Framework – At DIGIOTAI, through our team of experienced ML and NLP SMEs, we have developed an AI framework which can easily be customized and tweaked based on Industry regulations and needs
Core Modules
– Setting up a central console and configure technology preferences, processes and Industry Standards
– Set up an Explorer engine, to provide information search and analytics capabilities which is required to explore structured and unstructured contents
– Set up interactive dashboards for data visualisation for operational insights, correlation and anomaly detection
API Engines
– Set up Text Classifiers, to model content based on user-defined metrics and industry norms
– Defining Text Clustering APIs, to discover and garner meaningful subjects across contents by text grouping which is similar
– Set up Regression Modeling APIs, by using statistical techniques based on NLP and ML/DL principles, to garner relationship insights between variables, used to make certain predictions and forecasting
– Extensive NLP and ML/DL Engines, developed based on custom algorithmic data models to garner insights from structured or unstructured data and provide relevant outcome rankings
– Deep Insights leveraging extended ML models to analyse large amounts of structured and unstructured data to get deeper Operational Insights, identify data trends, correlations and anomalies
Learning Models
– Based on the findings from the above 2 buckets, derive Pre-Configured Learning Models for specific technology, process or industry buckets