AI integration and automation
Support triage, intake, invoice matching, lead research. One workflow eats hours of your team’s week.
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.
- Build
- Scoped in the audit
- Starts with
- A one-week audit, then a one-week blueprint
- Build price
- Fixed at the end of the blueprint
- Models
- OpenAI, Anthropic or open-weight
- Your tools
- Stay. The AI goes inside them.
Who it’s for
The audit ranks what’s worth automating. Sometimes the answer is don’t build.
A good call when
- One workflow eats hours of your team’s week, and you can point at it.
- The work happens in a CRM, support desk or ops tool you want to keep.
- You need to know when the system is wrong, not just that it ran.
- Your data has to stay in your accounts, or in a particular cloud region.
Not the right fit when
- A rule would do the job. Then we’ll say so, and it won’t need a model.
- There’s no real workflow or team behind it yet. Build engagements fit best when there is.
Not sure which kind of build you need? Start with the audit
What’s included
Everything sits inside the tool your team already opens in the morning. Nobody learns a new app.
LLMs, chosen per task
OpenAI, Anthropic or open-weight models. The model stays your choice.
Retrieval (RAG)
Answers drawn from your own documents and records, not the model’s memory.
Workflow automation
Wired into your CRM, support desk or ops tool, where the work already happens.
Monitoring
You see what the system did, case by case, in production.
Evals
Tests that check output against known-good answers, so you know when it’s wrong.
A data-flow document
Least-privilege access, and exactly what is sent to which model provider and why.
- 01Ticket arrivesin your support desk
- 02Classifywhat it is, how urgent
- 03Retrievefrom your own docs (RAG)
- 04Drafta reply, in the ticket
Monitoring and evals
How it runs
The audit finds the workflow worth automating. The blueprint designs how it fits your tools and fixes the build price.
- 1 week
Audit
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.
- 1 week
Blueprint
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.
- Set in the audit
Build
Scoped in the one-week audit, with a fixed build price set at the end of the blueprint. A working build, demoed to you every week.
- Ongoing
Run
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 know which workflow is worth automating, how it fits your tools and what the build costs, in writing. You can walk away with all of it.
- A working build every week
- You own the code
- We run it, or hand it over
FAQ
If your question isn’t here, ask it when you write. We reply within one business day.
Do we have to switch tools?
No. We put LLMs, retrieval (RAG) and workflow automation inside the CRM, support desk or ops tool your team already works in. Your team keeps working where it works today.
How long does an AI integration take, and how is it priced?
It’s scoped in the one-week audit, which is priced as a fixed fee before you commit. A one-week blueprint follows, and at the end of it the build price is fixed in writing before we write code. You see a working build every week after that.
How do we know when the AI is wrong?
Every integration ships with monitoring and evals. Evals are tests that check the system’s output against known-good answers, and monitoring shows what it did in production, so you know when it’s wrong instead of finding out from a customer.
Which models and technologies do you work with?
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.
Where does our data go?
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.
What happens if the audit says we shouldn’t build anything?
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.
A few lines is enough. We reply within one business day.
Or write directly:hello@dynode.ai+1 332-456-0669