Imagine a world where AI rescues us from boring, repetitive routine tasks — freeing our minds to unleash creativity and drive unstoppable business growth. Yet in our current reality, we are still quite far from that ideal, as new data projects continue to overwhelm us even more.
Ikidata was founded to bring that long-awaited vision to life.
Working with data is truly rewarding, but something still felt off. We constantly perform repetitive, tedious tasks, and as the amount of data grows, so do our workloads. AI was supposed to free up resources for us so that we could focus on complex business challenges. In reality, it has led to even more firefighting. This core issue had been bothering me for a while — how can we truly take data automation to the next level?
The arrival of GenAI changed everything. At first, LLM models were just fun chat companions with minimal practical benefits. However, as LLM models evolved, their use cases expanded dramatically. Today, we've reached a level where we can start integrating them into business automation. And this is exactly where the idea for Ikidata was born — to bring a completely new kind of automation to the market by leveraging GenAI Agents.
Standardized? Let's automate it.
Every process is an opportunity for automation. Start by understanding the challenge, break it down into tasks that are ripe for automation, and then leverage GenAI agents to tackle one step at a time. Here's a more detailed article on the process: GenAI Agents: From Hype to Real Business Value. Once the process has been thoroughly mapped out and the value-adding automation opportunities identified, it's time to move from planning to actual implementation. With the right infrastructure in place, integrating these solutions into your business processes is simpler than you might think. You can read more about GenAI agent possibilities in Databricks here: GenAI Agent Architecture in Databricks. Ultimately, getting started with GenAI agents is relatively quick, but the same challenge exists as in data science—projects tend to stretch out and require exponentially more resources when aiming for perfection. That’s why it’s best to avoid overly ambitious projects at the start. Instead, focus on low-hanging fruit, gradually fostering a cultural shift toward automation.
Databricks GenAI Agent Developer
Simplicity is beautiful — there's no denying that. Instead of building integrations and data pipelines across ten different systems, each with its own unique SLAs, sometimes even managed by separate internal teams, you end up with a chaotic mess. And when things go wrong, good luck figuring out at which stage the data got corrupted, who is responsible for fixing it, what needs to be done and who maintains it all. That's why solutions should be built as close to the data as possible with a simple governance model. This is where Databricks truly shines.
By now, most organizations have already established their data platform on Databricks, maintaining their data there. But instead of just using it for reporting and analytical needs, it’s time to start integrating business processes into Databricks by leveraging GenAI agents. This is where things get really rewarding and fun — unlocking entirely new kinds of value. To help you get started, we've outlined different stages of maturity and the best starting points for implementation. Check it out here: GenAI Agent Solution Strategies.
Ikidata is a Databricks GenAI agent developer company, a pioneer in GenAI Agent automation, providing deep insights into this emerging technology from technical, architectural, and business perspectives. We make it simple to bring your ideas to life.
Written by Aarni Sillanpää
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