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

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.

What data do you need access to?

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.

Will this work with our existing systems?

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.

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

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.

Who owns the code and workflow after the sprint?

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.

Can you work with our internal AI or data team?

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

What LLMs do you use?

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.

AI Automation Sprint | Build Working AI Workflows in 30 Days

Why AI Projects Fail to Reach Production

The demo works. You've seen GPT-4 summarise documents, classify emails, and generate responses in a Jupyter notebook. The potential is obvious. Then you try to turn it into something your team actually uses — and it falls apart.

The demo was built on clean sample data. Production data is messy. The prompt that worked in testing fails on edge cases in real use. Nobody thought about latency, error handling, cost per call, or what happens when the LLM returns something unexpected. The security team has questions nobody can answer. Three months later, the POC is still a POC.

Techseria's AI Automation Sprint is designed for exactly this problem. We take your highest-value AI use case — the one with a clear business case and a realistic data source — and build it to production standard in 30 days. Not a demo. Not a prototype. A working system your team can use on Monday morning.

What We Build

Document processing and extraction — invoices, contracts, forms, reports
Email and message classification, routing, and automated responses
Internal knowledge base and document Q&A (RAG)
Structured data extraction from unstructured inputs
Automated report and summary generation
Approval routing and exception flagging workflows
AI-assisted data entry and validation
Integration workflows connecting AI output to your ERP, CRM, or database

How the Sprint Works

Week 1 — Discovery and Architecture

We start by understanding the problem in detail: what data goes in, what outcome is required, what the current manual process looks like, and what success means in measurable terms. We define the architecture — which LLM, which embedding model, which vector store, how it connects to your existing systems. By end of week one you have a detailed technical spec and a working skeleton.

Week 2 — Core Build

We build the core workflow: data ingestion, LLM integration, prompt engineering, output parsing, error handling, and logging. We work against real data from your environment, not sample data. By end of week two you have a working system — not production-ready yet, but functional against your actual inputs.

Week 3 — Integration and Hardening

We connect the workflow to your real systems — the email inbox, the SharePoint folder, the ERP queue, the API endpoint. We harden the prompt design against edge cases in your real data. We add retry logic, fallback handling, cost controls, and audit logging. We test against real-world scenarios.

Week 4 — Deployment and Handover

We deploy to your environment — cloud-hosted or on-premises. We document the system, train the users who will manage it, and write the runbook for your technical team. We leave you with a live, documented, maintainable system — and an optional retainer for ongoing iteration.

Pricing

Discovery Workshop — £1,500–£3,000

Half-day or full-day session to map your automation opportunities, prioritise the highest-value use case, and produce a technical specification and cost estimate for the sprint. Deductible from sprint cost if you proceed.

AI Automation Sprint — £7,500–£15,000

30-day fixed-price engagement. One or two Techseria AI engineers, working from discovery to production deployment. Price depends on complexity — number of integrations, data sources, compliance requirements, and deployment environment.

AI Automation Retainer — From £2,000/month

Post-sprint support and iteration. Covers prompt tuning, model updates, new workflow additions, performance monitoring, and incident response. Typically three to six months, then reassessed.

Technologies We Use

LangChain and LlamaIndex for orchestration
OpenAI (GPT-4o, o1), Anthropic (Claude), Google (Gemini)
Azure OpenAI for enterprise compliance requirements
Pinecone, Weaviate, Chroma for vector storage
Azure, AWS, or on-premises deployment
Python with FastAPI or Django for workflow APIs
Integration with Microsoft 365, ERPNext, Salesforce, and custom APIs

Why Techseria

We build for production, not demos — every sprint ends with a deployed, documented system
Real data from day one — we work against your actual inputs and edge cases, not clean samples
Full-stack delivery — AI engineering, API integration, cloud deployment, and user handover in one engagement
Microsoft Solution Partner — experienced with Azure OpenAI, Azure AI Search, and enterprise compliance
Fixed price — you know the cost before we start; no hourly billing surprises

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