- Identify business use cases
- Interpret as technical & product problem statements
- Craft solutions
Workflow & Process
Capture & create data through audio & video analysis. Classify videos based on enriched metadata such as image / video guidelines and more.
Identify and extract relevant information from documents using OCR and NLP. This can be done even when the data structure is changed.
Create robust data catalogs that are organizable for queries and allow for team members to build their own models over time.
Automate the process of monitoring and removing content that is inappropriate or of poor quality.
Using Computer Vision and NLP, create enriched metadata for images and text based on domain-specific taxonomy.
Using historical data and robust real-time user profiles, predict demand for products and services and optimize resources as well as operational expenditure.
Build dynamic user profiles and understand every user’s unique behavior. This offers you a singular view of your customer across channels and touchpoints.
Target any new piece of content to the right cohort of users for maximum engagement. Personalize promotions for new products, services & content based on user profiles.
Drive more qualified leads and nurture your leads to faster conversions by user profile enabled lead scoring and sales enablement.
Enable higher user retention by facilitating user movement down the conversion funnel - be it onboarding, pre-assessment, or availing services - based on real-time knowledge of every user.
Leverage AI, along with programmable automation, to convert data extracted from documents into usable, structured formats, and for consumption by downstream systems.
Onboard & organize content faster using enriched metadata. Automate workflows for user onboarding with quality checks such as text & image moderation.
The three layers that unify data, processes and people
One Platform. Endless Possibilities.
Plug and play any of these capabilities to solve any business problem
Reduction is resource costs
Increased customer retention
Faster go-live through process automation
Of customer revenue contributed by Blox
30% - 50%
Lift in site wide conversion rate
20$ - 35$
ROI for every 1$ spent of us
40% - 60%
Lift in revenue per visit
Reduced time in data organisation processes
Increase in conversion rate with enriched data
Accuracy in extraction, enabling faster document processing
AI Maturity a measure of an organization’s wholesome ability to implement AI solutions at scale. The key to AI maturity, from exploring AI to transforming with it, is envisioning what that end-state could look like for the bisomess and envisioning a clear path to that vision from the company’s current state.
In conversation with over 100 AI Transformation leaders across industries & geos
“Tata Neu was built on three pillars - data, supply chain, and omnichannel. Data was the first pillar. We had a customer base of 150 million and 4800 physical touchpoints across the country. We wanted to harmonize all that data in one ecosystem, keeping security and privacy in mind, with utmost importance - and that was how Tata Neu was born.” he added, speaking of the inception of the app and how the data the 150-year-old conglomerate had acquired over the years helped them increase their stronghold in the digital space.
“It starts with building a base - breaking down a problem into smaller mini problems, assessing what’s in place and what must be brought together. It all starts with data - bringing all the data together from different sources in one data lake, ensuring they all have a unique identifier. Building a strong base is critical to start the personalization journey. Data will never be 100% correct. Not everything can be perfect, and that’s okay. Even if your data is just 80% perfect, you could still use it for personalization, as long as you deliver benefits and derive results
“I think there are two types of issues regarding data reliability - Structural Problems and Human mistakes. We can make rules to control human mistakes, but structural problems are bigger. The entity or individual that owns the data has to ensure that the data is trustable. There should also be somebody who’s unbiased, looking at the data, interpreting it, and presenting it to decision-makers. You get into problems when you lose the sanctity of this chain.”