CDS – faster, smarter court data journalism
.webp)
Court Data Solutions (CDS) revolutionised their AI-powered legal journalism capabilities by implementing DeepFlow.
Reducing iteration cycles from weeks to hours while eliminating dependency on engineering resources for content optimisation.
The challenge:
CDS wanted to offer generative-AI features that could turn complex court data into high-quality news stories. Their existing setup—linking many data components data and LLM calls—was slow to iterate and dependent on a team of engineers. Simple changes like prompt tweaks or model swaps could take weeks, and acting on user feedback was cumbersome.
They couldn't achieve this efficiently because:
- Their initial infrastructure was a complex web of disparate components.
- Data pipelines, LLM orchestration, storage systems. All requiring constant engineering oversight.
- Every iteration to improve story generation quality took weeks of development cycles.
- Testing new approaches meant mobilising engineering teams for each experiment.
- Customer feedback couldn't be rapidly incorporated into the AI workflows.
- The technical complexity created a bottleneck between business insights and implementation.
The Solution:
With DeepFlow, CDS replaced the rigid setup with visual agent-based flows. The team can now customise the process, swap agents, and iterate on feedback instantly without the need to employ a single engineer. Changes happen in hours, not weeks, and every step is visible in real time. See the Impact below, in this table.
The Solution:
With DeepFlow, CDS replaced the rigid setup with visual agent-based flows. The team can now customise the process, swap agents, and iterate on feedback instantly without the need to employ a single engineer. Changes happen in hours, not weeks, and every step is visible in real time. See the Impact below, in this table.
The Result: Mission-Critical Infrastructure
Court Data Solutions cannot operate without DeepFlow. What started as a single workflow solution became the backbone of their AI strategy. The platform didn't just solve problems—it changed how CDS thinks about AI implementation.
Key wins:
- Months of engineering time saved annually
- Higher content accuracy through rapid iteration
- Faster customer response = happier customers
- Innovation at the speed of thought
CDS now
- Swaps AI agents based on performance—instantly
- Builds custom agents without third-party help
- Uses DeepFlow for document automation and daily operations
- Plans to transform all manual workflows with the platform
Next steps
CDS is already planning to deploy DeepFlow for other processes, including data ingestion pipelines for their B‑to‑B products and custom agents without adding engineering headcount.
Real research. Powered by DeepFlow.
Rebuild the way you work with AI, in just 3 days.
