TechGurus
Strategy Automation Intelligence
Client login ↗Book a Strategy Call
Services / Custom AI Tools
Service

Custom AI Tools

AI tools built specifically for how your business works, not a generic product you have to work around.

Custom ChatbotDocument ProcessorPredictive ModelFine-tuned AIAPI IntegrationInternal AI Tool
How it runs
Requirements Deep-Dive
We spend time understanding your problem: what you're trying to achieve, data you have, constraints, and success criteria.
Solution Architecture
Technical approach: which models, how to structure the app, data pipelines, and integration points.
Prototype & Validate
A working prototype tested against real business examples. You validate before we invest in the full build.
Production Build
Production-ready application with proper error handling, logging, and security, ready for real workloads.
Deployment & Handover
Deployed to your environment, load-tested, documented, and your team trained to maintain it.
Problems it addresses

If any of this sounds familiar, it is worth a conversation.

You've tried every AI tool on the market and none quite fit: generic, expensive, or can't connect to your data.

Your business has unique workflows or proprietary data that off-the-shelf AI isn't designed to handle.

You need an AI capability that gives you a competitive edge, not the same tool your competitors already have.

You've started an AI project internally and hit a wall: model accuracy or integration complexity.

What we deliver

A working outcome, not a slide deck.

01

Custom AI Application

A purpose-built AI tool (web app, internal dashboard, or API) designed around your exact workflow and data.

02

Model Training & Fine-tuning

Where the use case requires it, we train or fine-tune models on your data so the AI understands your domain and terminology.

03

API Integration

Your new AI tool connected to systems you already use (CRM, ERP, databases, third-party APIs) so data flows automatically.

04

Ongoing Support Plan

A documented support arrangement covering model updates, performance monitoring, and feature additions.

Delivery process

How an engagement runs.

STEP 01

Requirements Deep-Dive

We spend time understanding your problem: what you're trying to achieve, data you have, constraints, and success criteria.

STEP 02

Solution Architecture

Technical approach: which models, how to structure the app, data pipelines, and integration points.

STEP 03

Prototype & Validate

A working prototype tested against real business examples. You validate before we invest in the full build.

STEP 04

Production Build

Production-ready application with proper error handling, logging, and security, ready for real workloads.

STEP 05

Deployment & Handover

Deployed to your environment, load-tested, documented, and your team trained to maintain it.

Pricing approach: discovery is a fixed fee. Build work is quoted as a fixed scope and price once discovery is complete, so you decide with the numbers in front of you. Ongoing support is a monthly retainer you can stop at any time.

Questions

Frequently asked.

How is this different from an off-the-shelf AI product?+

Custom tools are designed around your specific data, terminology, workflows, and edge cases. Accuracy and fit are meaningfully better.

Do I need to provide training data?+

Depends. Some tools work on foundation models with prompting and RAG, no training needed. Others benefit from fine-tuning.

What tech stack do you use?+

Python and TypeScript, cloud-hosted models unless on-premise is required. Pragmatic choices for reliability.

Who owns the code, and what about the models?+

You own all the custom code and documentation outright, handed over to you in full, source and all, with no licence to keep paying and no lock-in. The underlying AI models are licensed from their providers (OpenAI, Anthropic, or open-source), and everything runs under your own accounts, so access is always yours. Any fine-tuning we do is deployed in your environment. When we're done, the code is yours to run, change, or take elsewhere.

How long until we see results?+

Prototypes in 2–3 weeks. Production in 6–12 weeks depending on complexity. Milestones agreed upfront.

Further reading: Cloud AI, or your own server? · 7 minute read

Tell us the process that is costing you the most time.

We will tell you honestly whether this is the right answer for it.

Book a Strategy Call