Prototypes · SaaS platforms · AI integration
Dynode is an AI-first software studio that takes working prototypes to production and puts AI inside the tools your team already uses. Senior engineers work alongside AI agents.
You built something people want to use. Now a pilot customer is waiting for logins, and the second one needs its own account, with its data kept apart from the first.
Product. Your demo, and everything a new user meets around it, in their language, right-to-left included.
Access. Each person who signs in sees what their role allows, and the audit log records who changed what.
Data. Every customer’s data stays apart from every other customer’s, and last night’s backup actually restores.
Money. Billing that survives a failed card and a refund.
Reliability. When something breaks at 2 a.m., you hear about it before a customer does, and the last good version is one step back.
AI safety. The model’s answers are tested before each release, and someone gets told when they start to drift.
What we build
Three kinds of work, and one way in: a one-week audit.
Prototype to production
We take what you have, whether a freelancer built it or you built it yourself with AI coding tools, and add what production needs: logins and roles, each customer’s data kept apart, billing, monitoring, and evals for the AI parts. The audit decides what we keep and what we rebuild.
Start with your prototype How this works: Prototype to productionSaaS platforms
Multi-tenant SaaS, client portals, internal tools, and apps built around the one process your business actually runs on. Roles, billing, an admin panel and hosting are part of the build, and AI goes in only where a model beats a rule.
Scope your platform How this works: SaaS platformsAI integration
Support triage, intake, invoice matching, lead research. We put LLMs, retrieval (RAG) and workflow automation inside the CRM, support desk or ops tool your team already works in, with monitoring and evals so you know when it’s wrong.
Point us at the workflow How this works: AI integrationAI audit
Start with the one-week AI audit. It’s a fixed price, and sometimes the answer is don’t build.
AI integration, running
A support ticket arrives. The system classifies it, pulls the right documents and the customer record, drafts a reply and checks its own confidence. Clear cases go out. Anything uncertain goes to a person.
Illustrative workflow · simulated
Tickets in
6
To a person
1
Weekly demos
You don’t wait three months for a reveal. Every week there’s a build you can click through, on your own data where you can share it.
How we work
Every project runs in the same four steps. The first two are short on purpose.
We read the code that exists and the data and workflows around it, then rank what’s worth building. If nothing on the list is worth it, we say so, and you keep the process map, the ranking and the reasoning.
We write down how the system will be built, what’s in scope and what ships in which week, then put a fixed price on the build. The blueprint is yours to keep, whether or not you build with us.
A working build, demoed to you every week, running on something you can click. 4–8 weeks to take a prototype to production, 4–12 for a new build.
Two ways to go. We run it, with hosting, monitoring and support on a monthly retainer. Or we hand it over completely: the code, the documentation, the eval setup and access to everything. It’s a choice, not a dependency we engineer in.
Two weeks in, you have an architecture, a scope and a fixed build price in writing, and you can walk away with all of it.
Start with the auditSenior engineers
AI agents
The alternatives
Every option here is the right call for someone. The last column says where each one stops, so you can see which one fits where you are.
| Option | A good call when | Where it stops |
|---|---|---|
| Keep building with AI tools | You’re still finding out whether anyone wants it. | When someone depends on it: a second customer, real payments, a security review. |
| A freelancer | The work is well defined and someone technical can review it. | When one person holds the whole system, with no review and no backup. |
| An hourly dev shop | Scope will keep moving and you’d rather pay for time. | When you need to know the build total before you start. |
| Hiring in-house | This becomes the core of your company for years, which is where you should end up. | When you need it live before a hire could start. We hand over the code, docs and eval setup so that hire can own it. |
 Dynode | You have a working prototype with a date attached, and you want the build price before the code. | Not the right fit while you’re still validating the idea. |
Who it’s for
For growing teams
For founders and growing companies with a prototype, a platform idea or a workflow that’s holding them back.
For enterprise
For larger organizations that need AI inside existing systems, with governance their teams can sign off on.
The defaults
These are the defaults on every engagement, whichever way you go after launch.
Our own product
Dynode built Dynvolt and runs it in production, with the same senior engineers, AI agents and weekly builds you’d get. It has its own site.
SCADA, AI forecasting and market bidding for utility-scale solar and battery plants.
dynvolt.com (opens in a new tab)FAQ
Still deciding? The audit is one week, and you keep the findings either way.
Start with the auditWe price the audit as a fixed fee before you commit. If it shows the build isn’t worth doing, you stop there and keep the findings. Otherwise a one-week blueprint follows, and at the end of it, two weeks in, the build price is fixed in writing before we write code.
One week of audit and one week of blueprint, then the build: 4–8 weeks to take a prototype to production, or 4–12 weeks for a new platform or app. You see a working build every week, so you’re watching the timeline rather than being told about it. If your date is closer than that, put it in the brief and we’ll say in our first reply what’s realistic.
No. It’s a common starting point, whether the prototype came from AI coding tools, a freelancer or another team. The audit tells you what to keep, what to rebuild and what it costs. What a prototype usually lacks is the layer underneath: logins and roles, each customer’s data kept apart, billing and monitoring.
Senior engineers, led by the person who designs your system. They make the architecture decisions, and they’re the people you talk to. AI agents work alongside them on implementation and testing, which is how a senior team ships in weeks. You deal directly with the people building it, from the first call to handover.
Then that’s the deliverable, and it’s the cheapest possible outcome for you. You keep the process map, the opportunity ranking and the reasoning, and you’ve spent the price of an audit instead of the price of a build that wouldn’t have paid for itself. Better to learn that in one week than after a build.
You do, unless you choose another licensing model, and whichever you choose is agreed in writing before work starts. You see a working build every week, so stopping never means starting from nothing. If we part ways, the handover includes the code, documentation, the eval setup and access to everything we set up.
Into your own accounts and infrastructure wherever possible, deployed in the cloud region your customers or regulators require. We work with least-privilege access, review the data flows during the audit, and document exactly what is sent to which model provider and why. The model stays your choice: we work with OpenAI, Anthropic and open-weight models.
Dynode (dynode.ai) is an AI-first software studio founded by Zoran Aleksikj. Dynode LLC is registered in the US, and the studio is also registered in North Macedonia and works with clients worldwide. We built and run Dynvolt, and you can reach us at hello@dynode.ai or +1 332-456-0669.
Build engagements fit best when there’s a real product or workflow with users behind it. If you’re still finding out whether anyone wants it, keep building with the AI tools. They’re good at exactly that stage. Talk to us when someone is about to depend on it: a pilot customer, a second account, a first invoice.
We’re model-agnostic: OpenAI, Anthropic and open-weight models, chosen per task. Around them, retrieval (RAG) pipelines and evals, integrated into the CRMs, support desks and internal tools your team already uses. Where a system needs to stay in a particular cloud region, it gets deployed there.
A few lines is enough. We reply within one business day.
A reply with a few questions about what you have.
A call with the engineer who would design your system.
An audit proposal with its price, or a plain answer that we’re not the right fit.
Rather write directly?
Dynode was founded by Zoran Aleksikj.