AI that fits the business you actually run.
Start in our cloud, run it on your own compute, or mix the two. We map one painful workflow first, then match the model, hosting and approval rules to it.
Choose where it runs before buying the tools.
Data sensitivity, task volume, uptime needs and human approval decide the path, not the model name.
- Who it fits
- Agents that touch customers or revenue and need reliable uptime, fast deployment and fewer technical decisions on your side.
- Cost shape
- No servers to run. Model routing sends each task to the right model instead of the most expensive one.
- Privacy shape
- Tools connect through controlled permissions, and risky actions stop for a person before they happen.
Find the model your workflow can run.
Pick the workflow, hosting preference, daily volume and the compute you already own. You get a model fit and a memory estimate, so the conversation starts with reality. It is a planning aid, verified against your real setup before anything is built.
These are the workflows we scope before recommending a model or a tool.
Lead response
Reply to new inquiries, ask qualifying questions, and sync the CRM before the lead goes cold.
Customer support
Answer common questions, route edge cases, and create a clean ticket history.
Back-office admin
Summarize emails, update records, prepare reports, and flag items that need approval.
Private document search
Turn policies, SOPs, proposals, and knowledge bases into a usable internal assistant.
Marketing operations
Draft review replies, content briefs, local posts, follow-ups, and campaign notes.
Workflow handoffs
Connect forms, inboxes, calendars, CRMs, spreadsheets, and approvals into one path.
- 1
Name the workflow
We start with one job: leads, support, reporting, documents, scheduling, or CRM updates.
- 2
Map the risk
We decide what AI can do automatically and what needs human approval.
- 3
Choose hosting
Cloud, self-hosted, or hybrid based on privacy, uptime, volume, and existing hardware.
- 4
Ship the first agent
We connect the tools, test with real records, and document how the team reviews the work.
Related paths
What is the best AI setup for a small business?
The best setup is usually one narrow agent connected to one painful workflow. If the task is public, high-volume, or uptime-sensitive, managed cloud is usually best. If the task involves private documents or heavy repeat usage, self-hosted or hybrid AI can reduce API costs and improve control.
Can we run AI on an old 16GB computer?
Sometimes, yes. A 16GB computer can run compact models for narrow jobs like drafting replies, searching small document sets, summarizing notes, or producing internal reports. It is not the right fit for every workload, but it can be useful when the workflow is scoped correctly.
Do small businesses need custom model training?
Most do not need training first. They need workflow design, clean data, retrieval, approval gates, and a model that fits the job. Training becomes useful when the same task repeats often, the language is specialized, or API costs grow enough to justify a smaller tuned model.
How does AnovaGrowth choose between cloud and self-hosted AI?
We compare task sensitivity, daily volume, latency needs, uptime requirements, hardware you already own, and the cost of API calls. The result is a practical deployment plan, not a generic list of model names.
How is this different from buying an AI chatbot subscription?
Subscriptions give you a tool. We design the operating workflow: what the agent reads, what it can change, when it stops for approval, where it writes back, and how the business owner checks the work.
Send the process, the tools and any hardware you already have. We will recommend the simplest path that can actually run.