Cognitive Copilots have multiple exciting capabilities that set them apart from ChatGPT or Microsoft Copilot. As a powerful technology, Cognitive Copilot is promising to accelerate businesses to next-level efficiency. So, how does it work?
In this blog, let’s dive deep into how Revenue.AI’s Cognitive Copilots work with data to see the magic behind it. We bring some critical questions from our clients and AI enthusiasts about Cognitive Copilot and data to discuss with our experts.
About Cognitive Copilot
Cognitive Copilot, by definition, is an AI cognitive tool that understands typed commands, automatically searching for insights from dashboards and various sources: different business knowledge bases (SharePoint, Confluence, PDFs, etc.), database, and data table outputs of analytical engines. Then, the Cognitive Copilot gives back to users accurate replies or suggestions. Cognitive Copilot can be natively integrated with various business communication platforms to send notifications to users.
Cognitive Copilot is a new digital workforce to empower businesses. By leveraging Large Language Models (LLMs) as part of its functionalities, Cognitive Copilot goes beyond just generating texts, images, and videos. Its capabilities include:
- Intelligent data retrieval
- Data-backed insights in real time
- Smart recommendations on best actions
How Revenue.AI’s Cognitive Copilot work with data
Revenue.AI’s Cognitive Copilots use LLMs as parts of their functionalities. Our Cognitive Copilots make sure that data from different inputs and sources is de-siloed and streamlined into one single source of truth, enabling insightful recommendations. So how do Cognitive Copilots retrieve data and should businesses be concerned about AI data security? Let’s go through some interesting questions about Cognitive Copilot and data we received from our training sessions.
“How is the data retrieved?”
“All databases can be collected via API. And the data is only retrieved unless company policy allows us to. For each and every company, there’s a separate discussion of how this can be done.” – Pawel Dadura, CTO, Revene.AI
During the Proof-of-Concept (PoC) phase, our experts usually work with companies as consultants. The process looks like this – we request some example data of one product brand or one category from our customers, run it through our ecosystem, and show how the results of how business efficiency can be boosted with Revenue.AI.
Do you know that with Revenue.AI, you can boost data access speed by 10 times? Book a free demo to see Cognitive Copilot for Commodity Trading or Cognitive Copilot for Tailored Promotion in action now!
“All my data in Salesforce, does your Cognitive Copilot retrieve data from there?”
The data is retrieved via API based on our clients’ consensus. We also ensure high level of security by using cutting-edge AI algorithm of metadata when working with the data. The system operates with meta information during the data retrieval process to protect data from cyber-attack.
“We’re not feeding any data to our customers to the AI engine. We use metadata to describe your data, and only work with metadata-based ecosystem that we build on our own and use for our core platforms. That way, we can make sure that none of your data is exposed to those cognitive engines run by Google, Microsoft, OpenAI, etc.” – Pawel Dadura, CTO, Revenue.AI.
With Revenue.AI’s Cognitive Copilot, whether it’s Salesforce or other business operation systems, whether it’s Teams or WhatsApp your company is using for communication, we can make sure native integration with those platforms.
“How does the Cognitive Copilot give back the answer of data tables?”
One of the outstanding capabilities that our Cognitive Copilot offers is business users’ capability to talk with data and dashboard. Imagine you are driving and need to check on prices of a competitor on the go. Instead of finding a place to park or reaching out to your phone to type in the command when it’s red light, you have an option to just talk to the chat, and the copilot gives you back the data, with dashboards and tables. From there, the copilot also suggests suitable recommendations.
One issue that has been huge and bothering, especially in the hype of AI, is the hallucination or artificial hallucination. This refers to the false and misleading information generated by Gen AI, and it happens quite commonly. In the context of business, the damage can be significant if the LLMs are employed for critical tasks, such as pricing and revenue management. Revenue.AI’s Cognitive Copilots, however, can well address this issue. We make sure the replies you receive are backed by relevant internal data, and ensure a high accuracy level.
So how does it work?
“Behind our ecosystem, there’re not only a specific data engine that is responsible for the baseline of the data curation steps (such as data cleansing, data merging, etc.) but also an analytical engine that is responsible for insight generation. That data engine is being used by Cognitive Copilots to feed them with relevant results.” – Gergo Fenyes, Data Science Lead, Revenue.AI.
Cognititve Copilot Maintenance
“Is there any maintenance required?”, you may ask. In one of our training sessions, we encountered this question with concern: If the client’s internal system is upgraded, do we have to come to them to update the data engine?
The answer is “No”.
“Behind the copilot, there’s the so-called self-service layer, which is like a setup environment, a low-code environment. If you store a particular set of data in a different data table, that configuration should be repointed. There’s no additional code change or anything besides that, and the update is relatively easy.” – Gergo Fenyes, Data Science Lead, Revenue.AI.
The updates of new functionalities and features are automatic as our ecosystem grows. Business users can enjoy the latest version of the Cognitive Copilots without worrying too much about maintenance.
Introducing Revenue.AI’s Cognitive Copilot Family
Spotting the trend of Cognitive Copilot ever since the first day we started 5 years ago, Revenue.AI had developed a family of Cognitive Copilot for different verticals and business use cases:
- RAI Base is the Cognitive Copilot for multi-purpose data analysis. With the ability to retrieve data from different sources into one single source of truth and notify latest updates, RAI Base can boost productivity by 90%.
- Zeta is the Cognitive Copilot for Commodity Trading. It’s efficient in task automation and streamlining Pricing & Revenue Management process to lower ~50% of operational costs.
- RAI Charles is our promo expert, helping business users realize risks and opportunities for effective promo campaigns and maximized ROIs. Let RAI Charles anticipate the next best action and recommend ideal outcomes for you, today.
- RAI Price is the go-to Cognitive Copilot for effective pricing strategies. The tool can run multiple pricing scenarios and help you figure out the ultimate pricing decision for thousands of SKUs. Ready to build your next efficient pricing strategy with RAI Price?
- RAI Dex is the virtual data steward from Revenue.AI and your ultimate solution to solve data complexity. RAI Dex is helpful in data cleaning, data enrichment, and data merging, making sure your data is easy to find, insightful, and can be reused.
- Allie is an Agile Copilot, the best friend of Scrum Masters, Product Owners, and Project Managers. Allie can simplify tasks and automate Agile best practices. This copilot can also integrate seamlessly across data sources and applications, making insights and action-making accessible on the go.
Cognitive Copilot can be a great solution to empower your team, boost efficiency, and generate more revenue, thanks to its powerful capabilities of handling data. To embark on the Cognitive Copilot journey, book a demo with us today!