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AI · Custom AI Solutions

AI built for your business.
Not a generic chatbot.

We build bespoke AI for your domain: retrieval-augmented generation over your own knowledge, copilots inside the tools your teams use, and model selection or fine-tuning, with evaluation and monitoring built in.

Before · generic AI
✕Generic answers with no sources
✕Knowledge buried in documents
✕Copy-paste into public AI tools
✕No way to measure quality
→
After · domain AI
✓Answers grounded in your content
✓Knowledge searchable in seconds
✓Secure AI inside your tools
✓Quality tracked with evaluations
Bespoke
Built for your domain
Grounded
Answers from your data
Measured
Evaluation & monitoring
Scalable
Production-ready
What is custom AI?

General models, grounded in your knowledge.

Off-the-shelf AI knows the internet, not your products, policies or customers. Custom AI connects capable models to your own data and workflows, so answers are accurate, sourced and useful for your specific work.

We combine retrieval, the right model for each job and a user experience your teams will adopt, then measure quality continuously.

Generic AI
Knows the internet, not your business
Generic AI
No sources, no quality measures
Custom AI
Grounded in your own knowledge
Custom AI
Cited, evaluated and monitored
Why it matters

What custom AI changes for your business.

Plain-English value: the outcomes teams actually feel.

Accurate answers

Responses grounded in your own documents and data, with sources.

Faster work

Drafts, summaries and research in seconds instead of hours.

Data stays protected

Private deployments and access controls instead of public tools.

Improves over time

Monitoring and evaluation drive steady quality gains.

How it works

Four moving parts of a custom AI solution.

STEP 01

Knowledge & retrieval

Your documents and data indexed so the model can find the right passages.

STEP 02

Model

The right model for the job, prompted or fine-tuned for your domain.

STEP 03

Experience

A copilot, search or assistant inside the tools people already use.

STEP 04

Evaluation & monitoring

Test sets, feedback and dashboards that keep quality measurable.

What we build

AI shaped around your work.

Knowledge assistants

Ask questions of policies, manuals and product documentation and get sourced answers.

Copilots in your apps

AI assistance inside Salesforce, portals or internal tools, where work happens.

Document intelligence

Extract, classify and summarise contracts, invoices and forms.

Analytics assistants

Ask questions of your data in plain language and get charts and summaries.

Content generation

On-brand drafts for proposals, emails and product content, reviewed by people.

Humans in control

Answers you can check.

Our solutions cite their sources, say when they are unsure and keep people in the loop for decisions that matter. Quality is measured, not assumed.

Cited sources
Answers link back to the documents they came from.
Human review
People approve outputs where the stakes are high.
Access controls
Users only retrieve content they are allowed to see.
Quality evaluations
Accuracy and safety measured on test sets before and after release.
Engagement

From idea to AI in production.

01

Discovery

Week 1

Define the use case, users, data sources and how success is measured.

02

Data & retrieval

Weeks 2-3

Prepare, clean and index the knowledge the solution relies on.

03

Build

Weeks 3-5

Model, prompts and user experience, iterated with real users.

04

Evaluate

Weeks 5-6

Accuracy, safety and cost tested against agreed targets.

05

Deploy & improve

Launch

Production rollout with monitoring and a roadmap for improvements.

What we deliver

End-to-end custom AI delivery.

RAG & Retrieval

Chunking, embeddings, hybrid search and re-ranking tuned to your content.

Model Selection & Fine-tuning

Choose, prompt or fine-tune models for quality, cost and data residency.

Copilot UX

Assistants and copilots designed for adoption inside existing tools.

Evaluation & Monitoring

Test sets, feedback loops and dashboards for quality, cost and usage.

Salesforce & System Integration

Connect AI to Salesforce, Data Cloud and your internal systems.

Security & Governance

Private deployment options, access control and responsible-AI policies.

The stack Models, retrieval and platforms we build with.
OpenAI Anthropic Claude Google Gemini Open-source models LangChain LlamaIndex Vector databases Salesforce Data Cloud Azure / AWS / GCP Python
Custom AI at work

Custom AI use cases, by industry.

Financial Services

Policy & product assistant

Staff get sourced answers from product terms, policies and procedures.

Sourced answers
Healthcare

Clinical document summaries

Summarise long documents for staff, with human review.

Faster review
Technology & SaaS

Support knowledge copilot

Agents find answers across docs, tickets and release notes.

Quicker resolution
Manufacturing

Technical manual search

Engineers query manuals and specifications in plain language.

Seconds to find specs
Why iTech for custom AI

Production AI, not science projects.

AI plus enterprise data

AI engineers who also know Salesforce and enterprise systems.

Measured quality

Evaluation built in from the first sprint.

Responsible by default

Privacy, access control and human review designed in.

Production focus

Deployment, monitoring and support, not just prototypes.

FAQ

Custom AI, answered.

Retrieval-augmented generation: before answering, the system retrieves relevant passages from your own documents and data and gives them to the model, so answers are grounded and can cite sources.
Often not. Good retrieval and prompting solve most use cases. Fine-tuning helps for specialised language, formats or cost at scale, and we recommend it only when it pays off.
We design for providers and deployment options that keep your data private and do not train on it, including private cloud deployments where needed.
We agree test sets and targets up front, evaluate accuracy and safety before release, and monitor quality and user feedback afterwards.
Yes. We build copilots and assistants inside Salesforce and connect to Data Cloud, as well as in portals and internal tools.
A focused first solution typically takes around six weeks to production. A proof of concept can validate the idea sooner.

Turn your knowledge into an AI advantage.

Book a free AI discovery call. We will assess your use case, data and the fastest route to production.