I have an idea
Turn it into a working product.
Scope the idea, test a prototype and build the product around what you learn.
Build my idea ↗Scoped problem? A working prototype in as little as 1–3 days.Production timelines depend on integrations, data, security, risk and scope.
Applied AI systems · Automation · Product engineering
From problem to working AI — fast.
Tell us what is slow, repetitive, expensive, confusing, disconnected, or missing. We design and build the website, app, AI agent, voice system, knowledge system, or automation that solves it — then teach your team how to run it.
Start here
Get a first workflow sketch to review. No contact details needed yet.
Your data stays yoursYour provider accounts, where practicalVisible AI costsTraining and handoff
Start with the outcome
You do not need to know what AI you need.
We work backward from the problem and choose the simplest system that can solve it reliably.
My team repeats too much work
Give time back to your team.
Connect intake, documents, follow-up, scheduling and reporting.
Automate the work ↗Customers get stuck
Make the next step easier.
Help customers find answers, choose a service and reach the right person.
Improve customer experience ↗Our knowledge is scattered
Find answers in your own information.
Bring documents, policies and product knowledge together with source links and permissions.
Make knowledge useful ↗Our AI is unreliable or expensive
Make the system dependable.
Find failure paths, control usage costs and add checks before important actions.
Fix our AI ↗I do not know where to start
Start with the work.
We study the workflow and identify a useful first build, including when ordinary software is enough.
Audit our workflow ↗Engineering the whole workflow
One problem.
One connected system.
We connect intelligence to the systems where work actually happens.
- 01Customer / inputA request, document, event or question
- 02AI / rules / knowledgeUnderstand the context and apply your policies
- 03Your softwareCRM · email · database · booking · documents · payments
- 04Useful actionRespond · route · schedule · update · generate · alert
- 05Human when neededReview uncertainty, exceptions and important decisions
Everyday work, better connected
What could change in your business?
Illustrative workflows, shaped to your tools and approval requirements.
Lead intake
- Customer explains need
- Missing details collected
- CRM updated
- Team receives a summary
Company knowledge
- Employee asks
- Approved sources retrieved
- Answer cites evidence
- Access rules respected
Document processing
- Document arrives
- Data extracted
- Rules checked
- Exceptions reviewed
Product idea
- Describe the idea
- Scope one workflow
- Build a proof
- Decide the next step
From proof to production
See it before you bet on it.
A focused prototype tests the critical workflow before a larger implementation decision.
Understand
Define the problem, users and constraints.
Prove
Often 1–3 days for a clearly scoped prototype.
Decide
Test with the people who will actually use it.
A prototype is not a production release. Scope, fees and production requirements are agreed for each engagement.
Speed without shortcuts.
We work from first principles, use AI throughout the engineering process, reuse proven system patterns and prototype the highest-risk part first. That means less time in meetings and more time validating what actually works.
The first proof answers a focused question. Production still requires its own integration, security and reliability work.
Beyond the chat window
What can AI actually do?
These are building blocks. We combine only the ones your workflow needs.
Understand
Text, documents, images, voice and customer requests.
Find
Retrieve the right information from company knowledge.
Decide
Apply reasoning, rules and business policies.
Create
Text, reports, images, audio, code and structured information.
Act
Draft or send approved messages, update systems, schedule and route work.
Monitor
Watch queues, deadlines, system conditions and exceptions.
Escalate
Bring a person in when judgment or approval is required.
Mikisi Labs
We build AI systems ourselves.
Our platforms, experiments and operating workflows bring the engineering into focus.
Internal R&D · active development
AI Publishing & Audio Platform
- 01Book / textSource and generation
- 02LanguageTranslation and pronunciation
- 03SpeechReplaceable TTS engines
- 04VerifyAlignment and audio QA
- 05DeliverVerified audio to the reader
A multi-stage system for book and audio experiences, combining text generation, translation, pronunciation, speech, verification and delivery.
View systemInternal R&D · foundation & system design
Marketing Intelligence Engine
- 01SourcesDocumented evidence
- 02RetrieveRelevant principles and context
- 03ReasonStructured direction
- 04ValidateClaims, conflicts and constraints
- 05ReviewOwner decision before creative use
An internal foundation for evidence-led marketing: source registries, structured briefs, validation rules and a design for controlled reasoning.
View systemMikisi-owned venture · production operations
Commerce & Product Systems
- 01OrderPayment event
- 02VerifyStock and product details
- 03FulfillSupplier coordination
- 04TrackShipping updates
- 05RespondCustomer update or escalation
Catalogs, merchandising, supplier coordination, shipping updates and customer communication for Mikisi Jewelry.
View systemWho we work with
Different teams. Real problems.
Founders
Turn an idea into a working product.
Businesses
Automate workflows and improve customer experiences.
Professional teams
Use documents, knowledge and AI with clear controls.
Enterprise
Integrate reliable AI into existing operations.
Product & engineering teams
Build or productionize AI features and infrastructure.
Build → integrate → document → train → transfer
Built for you.
Understandable by your team.
Your team learns how to use the system, supervise AI decisions, manage cost and maintain day-to-day operations.
Practical answers
Before we build.
What does a project cost?
Cost depends on scope, integrations, data and the risk of the workflow. We agree the first useful proof, its fee and deliverables before work starts. A production build is scoped separately.
Do we own the system?
Your data stays yours. Code, intellectual property, third-party licenses and handover are made explicit in the project agreement. Client-owned provider accounts are used where practical.
Can you work with sensitive company data?
We first agree what data is needed, who may access it and where it may be processed. Access controls, retention and deployment choices follow that review. Do not share sensitive records in this initial form.
What happens after the prototype?
We review the proof with you and decide whether to continue, change direction or stop. Production work adds the required integrations, security, testing, monitoring and training.
Can you replace or connect to our existing software?
Either may be possible. We start by understanding what works today and connect to existing tools where practical. A replacement or migration needs its own scope and continuity plan.
Can you work with our developers?
Yes. We can work alongside your team on architecture, implementation, evaluation or production hardening, with agreed ownership and delivery responsibilities.
Do we need an AI provider account?
Many engagements use accounts you own and pay directly, so usage and costs remain visible. We agree the provider and operating arrangement before implementation.
Can you use open-source or self-hosted models?
Yes, where they fit the quality, licensing, infrastructure and privacy requirements. We evaluate them alongside hosted APIs; self-hosting brings operating responsibilities as well as control.
What if the project does not need AI?
We will say so. Rules, integrations and conventional software are often the right answer. The objective is to solve the problem.
A useful next step
Bring us the problem.
We build the system.
You do not need a technical specification. Tell us what happens today and what you want to change.