AI inside the tools you useAI integration and custom AI development
We connect models like ChatGPT, Claude and Gemini to your website, CRM, app or internal systems, so AI works on your data, inside your workflow, under your control.
WHAT IT DOESLOG
Customer record
→ Summarised, next step suggested
Product catalogue
→ Descriptions drafted for review
Your own app
→ AI feature built in
Team ChatGPT use
→ Moved to a secure workspace
“Everyone on the team pastes things into ChatGPT. Nothing is connected, nothing is saved, and nobody knows what data went where.”
SOUND FAMILIAR?
What is AI integration?
AI integration means building AI into the software you already use, instead of copying and pasting into a separate chatbot. We connect models such as OpenAI’s GPT models, Anthropic’s Claude or Google’s Gemini to your website, app, CRM, shop or internal tools, so AI can draft, summarise, search, classify and answer using your own data, inside your own workflow. You get the benefit of AI with your data, your rules and your costs under control.
Tamkoz provides AI integration and custom AI development for businesses and individuals. We define the feature in writing, test models from different providers on your real examples, build it into your systems with limits and logging, and hand over documentation and a cost dashboard. Everything is built so you can change models later without starting again.
THE JOBS IT TAKES ON
AI INTEGRATION
Customer record
→ Summarised, next step suggested
Product catalogue
→ Descriptions drafted for review
Your own app
→ AI feature built in
Team ChatGPT use
→ Moved to a secure workspace
Better model released
→ Swapped without a rebuild
What AI integration solves
Most teams already use AI. The problem is that it isn’t connected to anything.
Everyone copying and pasting into ChatGPT
→ AI built into the tools where the work and data already are.
Company data in personal AI accounts
→ A secure business workspace and integrations under your company’s control.
Your app or website feels behind
→ AI features your customers will use: smart search, writing help, recommendations.
Records nobody has time to read
→ Customer histories, notes and tickets summarised with the next step suggested.
Content written one item at a time
→ Product descriptions, listings and drafts produced in bulk, for a person to approve.
Not sure which model to trust
→ Models tested on your real examples and chosen on quality, privacy and cost.
Every integration comes with
Whatever we connect AI to, these come as standard.
INCLUDED
- Model tested on your examples✓
- Your data kept private✓
- Usage and cost limits✓
- Human checks where it matters✓
- A log of what the AI did✓
- Cost dashboard✓
- Easy to swap models later✓
- Documentation for your team✓
EXTRASNONE HIDDEN
Who needs AI integration?
Businesses and individuals who want AI working inside their own tools, products and data.
Software and app companies
AI features added to your product: assistants, search, summaries and automation.
Online shops
Product descriptions, search, recommendations and customer insights from your catalogue and orders.
Professional services
Notes, documents and client records summarised and drafted inside your practice systems.
Sales teams
CRM records enriched, calls summarised and next steps suggested where your team already works.
Publishers and marketers
Drafting, tagging and repurposing content at scale, with editorial checks.
Operations teams
Internal tools that classify, route and summarise the requests your team handles.
Founders and individuals
A prototype AI feature or tool built properly, ready to show customers or investors.
A GOOD FIT IF…
- Your team already uses AI tools informally
- You want AI features in your own website or app
- Your data needs to stay under your control
- You want the right model at a sensible running cost
What we build
A written feature brief
What the AI does, for whom, with which data, and how success is measured.
A model comparison
Candidate models tested on your examples, with quality, speed and cost side by side.
The integration itself
Built into your website, app, CRM or tools through proper APIs, not screen-scraping.
Safety rails
Usage and cost limits, logging, data minimisation and human checks where the output matters.
A secure team workspace
If your team uses AI day to day, a business account set up with sensible settings and guidance.
Documentation and support
How it works, how to change it and what it costs, plus support after launch.
How AI integration projects run
A clear brief and a fair model comparison come before any code.
- ORDER 001START
1×Define the feature
We agree what the AI should do, for whom, with which data, and how you’ll know it’s working, written as a short brief you can hold us to.
- ORDER 002BUILD
1×Choose the model
We test a few suitable models from different providers on your real examples and pick on quality, speed, privacy and running cost.
- ORDER 003CHECK
1×Build it in
We add the feature to your website, app, CRM or internal tools, with limits on cost and usage, logging, and human checks where they matter.
- ORDER 004GO LIVE
1×Hand over and support
Documentation, a dashboard of usage and cost, and support afterwards. Built so you can swap models later without starting again.
Models and systems we work with
We choose for the job, not for a partnership, and build so you can switch.
- AI MODELS
- OpenAI (GPT models)Anthropic (Claude)Google (Gemini)Open models you host
- WEBSITES AND SHOPS
- WordPressShopifyWebflowNext.js and custom sites
- CRMS AND BUSINESS TOOLS
- HubSpotSalesforcePipedriveMicrosoft 365Google Workspace
- APPS AND PLATFORMS
- iOS and Android appsWeb appsInternal toolsMCP servers
- DATA
- PostgreSQLSpreadsheetsData warehousesVector search
If your system has an API, we can usually connect AI to it. If it doesn’t, we’ll suggest the simplest workaround or tell you it isn’t worth it.
How much does AI integration cost?
Building the integration is a one-off job we quote in writing. Running it costs what the AI provider charges for the text the feature reads and writes, which you pay directly and which we keep as low as the job allows.
WHAT AFFECTS THE PRICE
How complex the feature is
A single summarise or draft button is small. A feature with many steps, tools and data sources is bigger.
Your existing system
Modern systems with good APIs are quicker to work with than older or closed ones.
Data and privacy
Public data is simplest. Personal or sensitive data needs more careful design and controls.
Model choice and volume
Bigger models cost more per use. Heavy use makes choosing an efficient model worthwhile.
Testing
Features whose output customers see need more testing and review than internal ones.
FROM THE PROVIDERS THEMSELVES
- AI providers charge per million tokens (roughly three-quarters of a word each). Anthropic’s smallest current Claude model costs $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100,000 tokens. Source: Anthropic.
- OpenAI publishes per-token prices for each model, from small, inexpensive models to its largest ones. Source: OpenAI.
CHECKED 10 OCTOBER 2026. PROVIDERS CHANGE THEIR PRICES, SO CHECK BEFORE YOU BUY.
YOUR QUOTE · FIXED AND IN WRITING
We quote the build in writing, in your currency, and estimate monthly running costs before you commit.
How long does it take?
A focused AI feature can often be built and live within a few weeks. Larger products are delivered in stages, each one usable.
Access to your systems and test data is the most common delay. We send a short list of what we need on day one.
TYPICAL TIMELINE
YOUR QUOTE HAS THE REAL DATES
01 BRIEFONE CALL
We agree the feature and look at your systems.
02 QUOTE AND MODEL TESTABOUT A WEEK
Scope and price in writing, with candidate models tested on your examples.
03 BUILDTWO TO SIX WEEKS
Integrated, tested and reviewed with you.
04 LAUNCH AND SUPPORTONGOING
Live with monitoring, cost tracking and help when you need it.
AI integration questions
Something else? Ask in the chat. A person answers.
What are AI integration services?
AI integration means connecting AI models, such as OpenAI’s GPT models, Anthropic’s Claude or Google’s Gemini, to the software you already use, so AI can work on your data inside your workflow. Examples include summarising customer records in your CRM, drafting product descriptions in your shop, adding a smart search to your website, or building an AI feature into your own app.
What does an AI development company do?
It designs and builds software that uses AI: features inside existing products, internal tools, assistants and agents. A good one also chooses the right model for each job, keeps running costs under control, protects your data, and tells you when AI isn’t the right answer.
Which is best: ChatGPT, Claude or Gemini?
It depends on the job. Models differ in writing quality, reasoning, speed, cost and privacy terms, and they change every few months. We test candidates on your real examples, choose the one that does the job best for the money, and build so you can switch later.
Can you add AI to our existing app or website?
Usually, yes. If your app or website can call an external service, we can add AI features to it, from a writing assistant in a form to smart search or recommendations. We’ll look at how it’s built before quoting.
Our team already uses ChatGPT. Why integrate anything?
Copying and pasting into a chatbot works for one person, but nothing is connected, saved or shared, and company data ends up in personal accounts. We can set up a secure team workspace under your company’s account and connect AI to your systems so the work happens where your data already is.
Is our data safe?
We build on business-grade services and settings where providers don’t train on your data, keep keys and access under your control, and send the model only the data each task needs. Where data must stay in a region or in your own cloud account, we design for that.
Do we need to fine-tune or train our own model?
Rarely. Most business features work best with a strong existing model, good instructions and access to your data through search (RAG). Fine-tuning helps for a narrow task or a very specific style, and we’ll recommend it only when tests show it’s worth the cost.
What is an MCP server, and do we need one?
MCP (Model Context Protocol) is an open standard that lets AI assistants connect to tools and data in a consistent way. An MCP server for your system lets assistants like Claude use it safely. It’s useful if you want AI assistants to work with your own software; most small businesses won’t need one yet.
How do you stop costs running away?
Every integration has usage limits, the cheapest model that does the job well, and a dashboard of usage and cost. You see the monthly running cost estimate before you commit, and alerts if usage jumps.
Further reading
GOES WELL WITH
- AI agentsCustom AI agents that read, decide and act across your tools: they research a lead, update your CRM, draft the reply and ask you before anything important goes out.
- RAG & AI knowledge basesA private AI assistant that answers from your own documents, policies and data, shows where each answer came from, and keeps your information yours.
- AI consultancyA clear, jargon-free look at your business and where AI would save time or win customers, and where it wouldn’t be worth it.
SOURCES · CHECKED 10 OCTOBER 2026
Put AI where your work already is.
Tell us which tool or product you want AI in, and what it should do. We’ll come back with a brief, a model recommendation and a written quote.