Three Essential Strategies to Transform Business Observability Using a Vector Database
Vector databases organize data based on any sequence of business conditions. Here are three ways they help generate insights, streamline operations, and harness the output of generative AI.
In 2013, KX CEO Ashok Reddy felt a sharp, stinging feeling in his right arm. At his local healthcare clinic, doctors guessed what was wrong. They tried steroids, epinephrine shots for allergies, and an MRI to rule out multiple sclerosis. After days of pain and panic, they solved the mystery: Ashok had been bitten by a spider.
If his doctors had observed Ashok’s activities the day his pain began, they might have noticed he took out the trash from where it was stored in a dank, dusty, dark garage — a great place for spiders to hang out. This insight might have helped doctors “guess spider” faster.
Without event-by-event insight, they triaged his condition based purely on his current symptoms. They guessed randomly. They were flying blind.
What can business leaders learn from Ashok’s spider bite?
Observability 101
In technology, this big-picture-seeing ability is called observability, or the ability to track external outputs directly back to internal root causes over time. Observability would have helped doctors see and analyze Ashok’s movements on the day a spider bit him and look for suspicious activities or patterns that might reveal insights.
This high-fidelity, ordered view of data is vital because almost none of our applications today are monoliths, and the best way to understand what’s happening is to knit together information from a wide variety of services spread over many databases, apps, and platforms.
Vector Databases and Observability Go Together Like Spiders and Cobwebs.
Vector databases are designed to store and analyze every dimension of business events in one place, arranged in chronological, logical, or any order you choose. But, ordered.
An ordered view of event detail, decisions made by AI algorithms, metadata, interaction with other applications, the state of reference data, and statistical data provides the essential context to understand what happened and why. These activity patterns help deepen our knowledge about time, space, and order. What led to our achieving their goal? What caused us to miss our target? Just before this machine broke, what signals can we learn from?
As you consider embracing a vector database for better observability, consider these three strategies to ensure your technology is powerful and performant enough to meet the demands of a modern business.
1: Capture Every Event You Can
Logs are the most common observable events, but that’s the start. True enterprise observability is to capture as many events as you can.
For example, finance trading systems can observe important patterns based on past market conditions, client order patterns, and profitability over time. And most importantly, they can use those observed sequences to predict the best move to make today.
Clinical trial research teams in healthcare can store step-by-step data on anonymized patient records, doctor-patient interactions, or clinical trial study data to identify signals about adverse events or opportunities to provide better care.
And in marketing, where demonstrating causation and tracking effectiveness remains elusive, organizations can capture a temporal view of customer interactions and infer patterns that indicate engagement or non-engagement to improve customer success or loyalty programs.
Typically, any organization in any business has thousands or millions of timely interactions that could be captured, observed, and leveraged for better insight.
2: Use a Vector Database as a Tape Recorder for Governance
A vector database is the business equivalent of a video tape player for business events, including the output of generative AI. Once stored, time-based queries and analytics can play actions back, frame by frame, to see what happened in slow motion.
From a technical operations perspective, the goal is to understand whether the services are working and what happened when. But from a business observability perspective, log data must be organized by time and interwoven with other metadata to understand the context in which it was created.
Nowadays, we store different types of data we might want to replay and analyze: AI-generated predictions, free text from customer conversations, social media interactions, IoT sensor data, and much, much more. These events may be stored in various formats, from JSON to numbers to unstructured text.
But most observability products only handle simple log data. A vector database allows any data type to be integrated with its notion of time to create a deep understanding of the business, not just technical operations and service health.
To make the most of generative AI, a vector database is vital. It can keep predictions and the business events that occur as a result in a single location, making it simpler to comprehend the effects of automated actions, suggestions, and notifications made by algorithms. This "AI decision recording" is crucial for AI governance. It allows companies to review past actions for AI forensics, governance, bias analytics, and mitigation. In industries that regulate the use of AI, this record can also help with compliance.
A vector database, in other words, provides the foundational time-based view of all data and AI output, helping you answer new, pressing questions and operate with a more predictive, prescriptive, and proactive point of view.
3: Use Observability for Automation
Observability isn’t just about “rewinding the tape” for forensic analysis. The ability to automate rests on providing an in-depth, comprehensive view of business processes, often in near real-time. So the third step to effective business observability is to deploy analytical systems in real-time operations.
For example, observability is critical in call center management applications that depend on having a temporal view of the last five times any given customer called your company, the touch points she had with your salespeople, and log data from her use of SaaS applications such as browsing payment information or new product promotions.
By creating this observability in a 360-degree view of each customer and accessing it in real-time, you can more safely automate any business, provide an audit trail for what happened, predict what may happen in real-time, and equip business operations teams to make good decisions, in the moment.
Three Lessons From a Spider Bite
By embracing the power of a vector database for better observability, you can unlock insights that can help your business make smarter decisions and improve outcomes. Whether you trade on Wall Street, develop new drugs in healthcare, or search for spider bites in a haystack of events, vector data is essential to stay competitive in today’s digital world.
For More About Observability & Vector Databases
The Valuable Lesson A Spider Bite Taught Me About Business Observability, by KX CEO,
A Comprehensive Guide to Vector Databases, by
KDB.AI, a leading vector database.