Service
AI solutions that save time and answer customers
We build AI that does real work for your business: assistants that answer from your own documents, tools that read and sort paperwork, agents that handle routine tasks, and predictions that support decisions. You get measurable time saved, with people in control.
- 1,200+ clients helped
- Building since 2010
- 15 services, one team
- 50+ technologies
At a glance
What we build
We put artificial intelligence (software that can read, write, search, and predict) to work inside your real tools and processes: assistants, document handling, search, and predictions, built with the checks that keep them dependable.
Problems we solve
Many teams have tried AI tools but cannot get them into daily work. They are unsure which kind of AI fits, what it will cost, and how to keep it safe.
Who we serve
Leaders and teams who want AI to do one specific job, such as answering questions, handling routine requests, reading documents, or spotting patterns.
How to choose
Start from the job you want done, not from the technology. The right kind of AI depends on whether you need answers, actions, document reading, or predictions.
- 1,200+Happy clients
- 1,500+Projects delivered
- 100+Engineers and designers
- 20+Countries served
- 22Certifications
Every project gets its own squad from our 100+ engineers and designers: a project lead, a product designer, and engineers matched to your stack, with the same people from kickoff to launch.
Our approach
AI that pays for itself
We use artificial intelligence (AI) for work that normally needs human judgment: reading documents, drafting replies, finding the right answer, or spotting a pattern. Machine learning, the part of AI that learns from examples instead of fixed rules, is one of the tools we reach for, never the starting point.
In business, AI is useful when the work involves language, documents, images, or patterns that are too messy for simple rules. It is less useful when a clear rule already does the job. A rule that says "send invoices over a set amount to a manager" does not need AI.
So the first question is not "how do we use AI?" It is "what job do we want done, and is AI the best way to do it?" We help you answer that honestly, then build the part that is worth building.
Kinds of AI
The kinds of AI work we do
Most business AI falls into a few kinds. Each one suits a different job.
Knowledge assistants
An assistant that answers questions using your own handbooks, contracts, and files. Staff stop searching folders and get an answer with the source shown.
Support assistants and chatbots
A helper for your website or inbox that answers common questions at any hour. It hands anything difficult or sensitive to a person.
AI agents
Software that can plan steps and use other tools to finish a task, such as checking an order, updating a record, and sending a reply.
Document processing
Tools that read invoices, forms, contracts, and scans, pull out the details that matter, and send them where they belong.
Predictions and recommendations
Models that learn from past records to forecast demand, flag risks, or suggest what a customer may want next.
Image, video, and speech AI
Software that understands pictures, video, or spoken words: reading labels, checking quality, or turning calls into notes.
Choosing
Which kind of AI fits which job
Start from the job you want done. The right kind of AI follows from it.
Which kind of AI fits which job
What do you want AI to do for you? Answer questions from our own documents: A knowledge assistant; Handle routine customer messages: A support assistant; Carry out a task from start to finish: An AI agent; Read invoices, forms, or contracts: Document processing; Predict what is likely to happen: A prediction model.
If: Answer questions from our own documents
Choose: A knowledge assistantFinds the right passage in your files and answers in plain language.If: Handle routine customer messages
Choose: A support assistantReplies to common questions and passes hard ones to a person.If: Carry out a task from start to finish
Choose: An AI agentPlans the steps and uses your tools to complete them.If: Read invoices, forms, or contracts
Choose: Document processingPulls out the key details and files them correctly.If: Predict what is likely to happen
Choose: A prediction modelLearns from past records to forecast or recommend.
How it works
How an assistant answers from your own documents
Many useful business assistants work the same way. They look up the right pages first and only then write an answer. This keeps the answer tied to your real information.
How an assistant answers from your own documents
A sequence of 5 steps. Your documents are prepared: Files are read and organized so they can be searched by meaning.; Someone asks a question: In a chat window, an app, or an inbox.; The right passages are found: The system looks up the pages most likely to contain the answer.; The AI writes an answer: It uses only those passages, not its general memory.; The sources are shown: A person can open the original and check..
- Your documents are preparedFiles are read and organized so they can be searched by meaning.
- Someone asks a questionIn a chat window, an app, or an inbox.
- The right passages are foundThe system looks up the pages most likely to contain the answer.
- The AI writes an answerIt uses only those passages, not its general memory.
- The sources are shownA person can open the original and check.
It uses your information
The answer comes from your approved documents, not from the AI guessing.
It shows its sources
People can check the original page, which builds trust and catches mistakes.
It knows when to stop
If the documents do not contain the answer, a well-built assistant says so instead of inventing one.
Choosing a route
Which route fits you?
There are three ways to bring AI into a business. They differ in cost, control, and effort.
How much do you need the AI to fit your own systems and information?
Choose this when
Your need is general, such as drafting emails or summarizing meetings, and it does not touch sensitive or specialist information.
- What you get
- A quick start and low cost, with the tool's features as they are.
- Keep in mind
- You have limited control over where your information goes, and the tool will not know your processes.
Choose this when
You want AI to work with your own documents, records, or software, but the job is well defined.
- What you get
- An assistant or helper wired to your information, with your rules, permissions, and a record of what it did.
- Keep in mind
- It needs clean, organized information and someone to check quality over time.
Choose this when
AI is central to your product or process, or you need behavior and controls no ready-made tool offers.
- What you get
- A system designed around your job, with testing, monitoring, and clear human oversight built in.
- Keep in mind
- It is the largest investment. Start with a small, measurable version before committing.
Choosing the right approach
How we pick the right approach
We use AI where it adds the most value: reading unstructured documents, answering questions, and making suggestions. Where a simple rule or a connection between systems does the job, we use that instead, because it is cheaper to run.
You get the most reliable solution for the job, measured against real results.
- The task follows clear, fixed rules.
- A wrong answer would be costly and no person will check it.
- You do not yet have the information the AI would need.
- Nobody can say what a good result looks like, so it cannot be measured.
Safe and useful
Making AI safe, accurate, and under control
A useful AI system is one people can trust. These are the four things we design for.
Your information
- We decide what the AI may see, and who may see its answers.
- Sensitive information stays within your rules for privacy and access.
Accuracy
- We test the system on real examples before it goes live.
- We keep measuring quality afterward, because models and information change.
People in control
- A person reviews decisions that matter.
- Every action is recorded, so you can see what happened and why.
Cost and change
- We estimate running costs before you commit.
- We plan for change, so a better model can be swapped in without a rebuild.
How a project runs
How an AI project runs
We start small, measure early, and grow only what works.
Pick one job
We choose a single, specific job with a clear measure of success, such as time saved or questions answered correctly.
What it produces
- One-page goal
- How success will be measured
Check the information
We look at the documents or records the AI would use, and fix gaps before building.
What it produces
- Information review
- List of what the AI may use
Build a small version
We build a working version for a few people, using real examples.
What it produces
- Working prototype
- Test results
Measure honestly
We compare results with the goal, including where it fails, and decide whether to continue.
What it produces
- Quality report
- Go or stop recommendation
Release with safeguards
We roll it out with review steps, limits, and monitoring in place.
What it produces
- Live system
- Monitoring and alerts
Improve and look after it
We keep checking quality and cost, and update the system as your needs and the technology change.
What it produces
- Regular quality checks
- Updates and fixes
Technology
The models and tools we build with
For your developers and IT lead: our choices on models and providers, giving a model your information, orchestration and tools, and evaluation and monitoring, and the reasoning behind each.
We work with leading AI model providers, including OpenAI, Anthropic Claude, and Google Gemini, and with open models such as Meta Llama and Mistral. The right model depends on the task, the cost, the speed needed, and where your information may be processed.
The assistant pattern shown above is often called RAG (retrieval-augmented generation). Documents are split into passages and turned into numbers that capture meaning. These are stored in a vector database such as Pinecone, Qdrant, or Weaviate. At question time the closest passages are retrieved and passed to the model.
Frameworks such as LangChain and LlamaIndex help connect models, search, and tools. For agents, we define exactly which tools an agent may use, with limits and approval steps.
- A test set of real questions with approved answers.
- Automatic checks for accuracy, unsafe output, and cost per answer.
- Logs of inputs, sources, and outputs, with sensitive details protected.
- Alerts when quality drops or costs rise.
What it looks like
See the AI systems we build
These pages describe the systems in more detail: how they are put together and what choices are involved.
- AI solutionsAssistants, document readers, and prediction tools built around a specific business job.
- AI agentsSoftware that plans and completes multi-step tasks using your tools, with people in control.
- Knowledge and content systemsSystems that organize your documents and make them searchable, answerable, and up to date.
Pricing and timelines
What AI work costs
Every project is quoted in writing after a short call. These ranges show where most projects land, so you can plan before you talk to us.
AI assistant on your content
A chat assistant that answers from your documents, site, or help center.
Typical range
$4,000 to $12,000
1 to 3 weeks from approved scope
AI feature in your product
Search, summaries, classification, or drafting built into the software you have.
Typical range
$8,000 to $18,000
2 to 4 weeks from approved scope
AI agent connected to your systems
An agent that reads, decides, and takes actions in your tools, with approvals.
Typical range
$16,000 to $32,000
4 to 6 weeks from approved scope
Custom model or AI platform
Trained models, evaluation, and the platform to run AI across the business.
Typical range
$40,000 to $100,000+
2 to 3 months from approved scope
The timeline starts once the scope is approved and we have what we need from you.
What moves the price
- Amount and quality of your data
- Systems the AI must connect to
- Accuracy and review needs
- Usage volume and running costs
Not sure which fits? Tell us what you need and we will send a fixed quote and timeline for your project. Read the full cost guide.
Get a quoteSelected work
AI & Machine Learning projects we have delivered
What clients say
In our clients' words
We were spending too much time sorting incoming tickets by hand, so we asked DECHY for help. Our agents still make the final call, but now they start in a better place.
James BennettCustomer Support ManagerRelayDesk Customer ServicesProfessional Services I was worried we'd end up sending customers canned answers. Amara at DECHY understood that. I like that unusual questions still reach a person who can actually help.
Chloe MartinCustomer Experience LeadKindred HomewareRetail
Common questions
Questions about AI projects
Do we need a lot of data to use AI?
Not always. Assistants that answer from your documents need good documents, not huge amounts of data. Prediction models do need enough past records to learn from. We check this in the first step, before anyone builds anything.
Is our information safe if we use AI?
It can be, if the system is designed for it. We decide what the AI may see, where information is processed, who may use it, and what is recorded. For sensitive information we choose providers and settings that fit your rules, and we say clearly when a use is not appropriate.
Will AI replace our staff?
Our approach is to take over repetitive work and support people, with a person reviewing decisions that matter. The goal is to give your team time for work that needs judgment.
Can AI make mistakes?
Yes. AI can be wrong or sound confident when it is not. That is why we test on real examples, show sources, keep people in the loop, and monitor quality after launch.
How long does an AI project take?
A focused AI assistant or document tool usually goes live in 1 to 4 weeks. AI agents connected to your systems take 4 to 6 weeks, and custom models or platforms 2 to 3 months. Most business AI projects cost $4,000 to $18,000; larger agents and platforms cost more.
How is AI different from automation?
Automation follows fixed rules to do repetitive work. AI handles work that needs reading, language, or judgment. Many projects use both: automation moves the work along, and AI handles the steps that need understanding. See our automation service.
Have a different question?
Tell us what you are weighing up and we will answer it plainly.
Ask a questionAlready a client? Email support@dechytech.com
Tell us the job you want AI to do
Describe the task, the information involved, and what a good result looks like. We will tell you which approach fits, what to try first, and whether AI is the right tool at all.