AI development company for the US and Canada
Autonoid builds custom AI agents, voice AI and SaaS platforms for North American teams. A working prototype in two to four weeks, a demo every week after that, and full source code handed to you at the end.
What we build
AI agents and copilots
Assistants that do the work rather than describe it. They read your data, call your tools, complete the task and escalate when they should. Colliq and InterviewPlan in the demo lab are both live examples of the pattern.
Voice AI agents
Inbound and outbound calling that understands intent, completes the action in your CRM or scheduler, and hands to a human with full context. Transcripts, summaries and outcomes for every call.
LLM and RAG integration
Retrieval over your own documents and databases, so answers cite your material rather than the open internet. Evaluation harnesses so you can see accuracy before it ships, not after.
Custom SaaS platforms
Multi-tenant products with workspaces, roles, billing and reporting. MarketingOS and NOVA in the lab are both full multi-tenant builds.
MVPs and prototypes
Idea to something clickable in two to four weeks, built so the good parts survive into production rather than being thrown away.
AI strategy and roadmaps
Which use cases pay back, in what order, and what has to be true first. Useful when the board has asked for an AI plan and nobody wants to guess.
How to tell a good AI partner from a bad one
Most AI projects stall somewhere between the demo and production. Four questions separate the teams who get past that from the ones who do not. Ask them of us, and of everyone else you are talking to.
Questions US and Canadian buyers ask
What kind of AI work does Autonoid take on?
Custom software with AI inside it. AI agents and copilots that take real action in your systems rather than just chatting, voice agents that answer and place calls, LLM and retrieval-augmented generation wired into tools you already run, and complete SaaS platforms, web apps and mobile apps. We build the product, not a demo that stalls at the pilot.
Are you a US company?
We operate from the United States and India. Contracts, invoicing and the commercial relationship sit on the US side. Engineering runs out of India, which is what keeps the cost sensible without putting a language or accountability gap in the middle.
How does the time difference work?
There is a daily overlap window with Eastern and Central time, and we run structured async handovers for the Pacific coast. In practice that means your morning stand-up has yesterday's work already in it. You get the engineers on the call, not an account manager relaying questions.
How much does a custom AI build cost?
It depends on scope, and anyone who quotes before understanding the scope is guessing. What we can tell you up front is the shape: a fixed-fee discovery sprint to define and de-risk, a custom-quoted product build, or a monthly retainer if you want an AI partner alongside your own team. Pricing comes after the discovery conversation, in writing.
How long until we see something real?
A working prototype in two to four weeks. Production launch typically six to twelve weeks after that, depending on integrations. You see a running demo every week in between, so there is no six-week silence followed by a surprise.
Who owns the code and the models?
You own the custom code, the documentation and the deployment setup, handed over on completion. No licence fee to keep paying, no dependency on us to keep it running. Where we use open source or our own pre-existing components, you get a perpetual licence to use them inside the delivered work.
How do you handle security and compliance?
Role-based access, audit logging, encrypted data in transit and at rest, and least-privilege access to your systems, designed in from the start. For regulated work we build to the framework that applies to you, whether that is HIPAA for health data, SOC 2 controls your customers expect, PIPEDA in Canada, or state privacy law such as the CCPA. We will tell you which controls we implement and which ones remain your responsibility, in writing, rather than waving a badge.
Can you run models privately instead of calling OpenAI or Anthropic?
Yes. Where data cannot leave your environment we deploy open-weight models such as Llama or Mistral on your own infrastructure or your own cloud account. Where a frontier model is the right call we use it with zero-retention settings. We are model-agnostic and pick on accuracy, cost and privacy rather than loyalty.
What happens if the pilot does not work?
You find out in weeks rather than quarters, and you keep the prototype and everything we learned. Discovery exists precisely so that a bad use case gets killed cheaply. We would rather tell you the automation will not pay back than bill you for building it.
Do you work with startups or only enterprises?
Both, but differently. Startups usually want a fixed-scope MVP that gets to market. Established teams usually want an agent or integration inside systems that already exist, with change management around it. The demo lab has examples of each.
Building in the Gulf instead? Read AI development for the UAE and GCC.
Let's build your AI product
Tell us what you want to build. We will come back with a plan, a prototype path and a clear estimate.