Precision in Data.
We specialise in data warehousing, data collection apps, and RAG agents.
But what does that practically look like?
We've found that in most cases, our interactions can be broken down into a few basic needs.
The questions our clients actually ask us.
Data Warehousing & Architecture
In the majority of these cases clients just want to have all of their data in a single place. They usually have some of the following issues:
- ?Their data is federated across multiple sources and systems.
- ?Their data lives in multiple Excel documents with multiple sheets, and multiple versions!
- ?Their data automation is a Key Individual and hopefully they don't get sick or go on leave.
- ?Should this be a warehouse or a lakehouse?
- ?How do we combine all our tabs and sources into one reliable dataset?
We help our clients with modern data architectures and automation: scalable, secure solutions built on 20+ years of finance and banking data experience.
Show me howData Collection & Automation Apps
Purpose-built apps that get clean data in at the source, before it becomes a spreadsheet problem:
- ?I have vibe-coded a data collection app, but now I want to actually deploy it. Where do I start?
- ?We need a custom app to capture field data and feed it into our warehouse.
- ?How do we automate the manual data entry that keeps breaking?
- ?We have IP that needs to become a data collection application. Where do we even start?
From prototype to production, we bring industry experience gained through blood, sweat, tears and a couple of 2am delivery deadlines.
Give us a handRAG & AI Agents
Retrieval-augmented agents placed where they have impact, not where they interrupt. Our clients range from novices to mature enterprises:
- ?Can a RAG agent answer this from our documents?
- ?Should my application even use AI?
- ?Can I use Claude with my Google infrastructure?
- ?How do I prove my AI is secure and compliant?
- ?I know there is Shadow AI Ops in my organisation, how do I monitor and manage it?
Hands-on expertise with Google ADK, multi-agent RAG, and the infrastructure you already have.
Sounds familiarSupporting Capabilities
Everything a data platform needs to run properly: cloud infrastructure, deployment, validation, and compliance:
- ?Is AWS Fargate better than Google Cloud Run for our use case?
- ?We are deploying our Python code manually. How do we automate this?
- ?We don't know if our application meets regulatory requirements like GDPR, POPIA, ISO27001 or SOC?
- ?What does scale-to-zero actually mean and should we have it?
With 8+ years of Google Cloud experience, we help you choose the right tools and run them properly.
I have my own questions
The Jakkalsdraf Methodology
Listen
We begin by understanding your business and operations, to ensure that we can deliver the best solution for you.
Design
We don't deliver at you, we will walk this journey with you. In every decision and recommendation we make, will require your input into your business and needs.
Validate
Not only will we cross validate the solutions with you, but we will also present options that you can choose from to ensure the final solution is tailored to your needs.
Act
Now we are ready to deliver with precision and accuracy. Ensuring the final outcome matches the initial Blueprint.
How we measure choices
Before work begins, we determine the actual cost of implementation, so you know exactly what you're committing to.
Blueprint
- Solution Design Document
- Functional & non-functional requirements
- Technical design
Backlog
- Detailed step-by-step view of the Blueprint
- When does what need to happen?
- What is the sequence?
Delivery Skill
- What kind of engineers?
- What are their skill levels?
- How familiar are they with the tech?
Duration
- How many tasks in the backlog?
- Which streams can run parallel?
- Skill of engineers × tasks