Question 1

Do we need to have a clear use case before we start?

Accepted Answer

Not necessarily. If you know AI could help but haven't pinpointed the highest-value use case, start with a Discovery Workshop. We'll map your operations, identify the best opportunities, and give you a prioritised shortlist with effort and impact estimates.

Question 2

What data do you need access to?

Accepted Answer

It depends on the use case. For document processing, we need sample documents and access to where they're stored — SharePoint, email, a file system, an API. We work with your IT or data team to set up secure access. We sign an NDA before any data is shared.

Question 3

Will this work with our existing systems?

Accepted Answer

In most cases, yes. We integrate with Microsoft 365, ERPNext, Salesforce, HubSpot, custom databases, and REST APIs. If you're running something more unusual, we'll assess it during discovery.

Question 4

What happens if the 30-day sprint isn't enough?

Accepted Answer

We scope carefully during discovery to ensure the sprint is achievable. If scope expands during build — which happens — we discuss the options: descope to stay on budget, extend the timeline, or continue on the retainer.

Question 5

Who owns the code and workflow after the sprint?

Accepted Answer

You do. All code is yours. We don't use proprietary frameworks that create a dependency. You can maintain and extend it internally, with another supplier, or with Techseria on a retainer.

Question 6

Can you work with our internal AI or data team?

Accepted Answer

Yes. We frequently work alongside internal teams — sometimes leading the build, sometimes supporting and transferring knowledge. We're flexible about the collaboration model.

Question 7

What LLMs do you use?

Accepted Answer

We start with what's right for the use case: GPT-4o for general reasoning and document tasks, Claude for long documents and instruction-following, Gemini for multimodal inputs. For enterprises with data residency requirements, we use Azure OpenAI.

FromAIDemotoWorkingWorkflow.30Days.

Why AI Projects Fail to Reach Production

Demos Lack Real-World Data Handling

Ignoring Operational Guardrails

Production Data Rigor

Hardened Workflows

Production AI workflows ready for Monday morning

Document Extraction

Email Classification

Internal Knowledge RAG

Data Entry Validation

API Integrations

How the Sprint Works

Discovery & Spec

Core Build

Integration & Hardening

Deploy & Handover

Predictable AI Sprint Pricing

Discovery Workshop

AI Automation Sprint

AI Automation Retainer

Technologies We Use

Ready to build production-ready AI?