SorakaService
AI Solutions
Retrieval, automation, and models applied where they earn their keep — and left out where they don't. We start by checking whether AI is even the right tool, then build systems with evaluation and guardrails so they survive contact with production.
Problems we solve
You probably recognise at least one of these.
Support answers the same questions all day
Your team retypes the same replies while the answers sit in documents no customer can find on their own.
The AI pilot never reached production
A demo impressed everyone in a meeting and then stalled, because no one owned the accuracy, cost, and privacy questions.
Manual review is the bottleneck
Someone reads every invoice, ticket, or application by hand, and the queue never actually empties.
You are not sure AI is even the answer
And you would rather find that out before spending six figures on a system that a few rules could have replaced.
What you get
Concrete deliverables, not a statement of intent.
Retrieval system (RAG)
Answers grounded in your own documents, with citations, so staff and customers stop searching by hand.
Workflow automation
Classification, extraction, and routing for the repetitive judgement calls that clog a queue.
Evaluation harness
A test set and metrics so you can prove the system is accurate before launch — and catch it when it drifts after.
Guardrails and privacy
PII handling, prompt-injection defence, and a clear boundary on what data ever leaves your systems.
Cost and model report
Which model, at what price per request, measured against the cost of a person doing the same task.
Monitoring in production
Accuracy and cost tracked over time, because a model that was right in March can drift by June.
How it works
A short, sequenced engagement.
- 01
Qualify
We look for a task with clear inputs, a measurable outcome, and enough volume to be worth automating. If AI is the wrong tool, we tell you at this step.
- 02
Prototype
A working version against your real data within weeks, measured against a plain baseline so the gain is visible.
- 03
Harden
Evaluation, guardrails, and monitoring turn the prototype into something you can put in front of a customer.
- 04
Operate
We watch accuracy and cost after launch and retune as your data and the models underneath both change.
Tech stack
Tools we reach for — chosen per project, never for their own sake.
- Python
- Claude
- OpenAI
- Llama
- pgvector
- LlamaIndex
- Qdrant
- Ragas
- FastAPI
FAQ
Questions we hear first.
Something not covered here? We answer within one business day.
Tell us what you are trying to ship.
A short scoping call, a written plan, and a fixed first milestone. We answer within one business day.