AI integration, done inside your company.
You don't need another AI strategy deck. You need the thing plugged into your CRM, your database and your billing, safely, by someone who's done it before. That's the job. We show up and do it.
// for 10–200 person companies with a real stack and a real mess
Who this is for
You already run software.
A CRM, maybe an ERP, a support desk, a few custom APIs and the spreadsheet that secretly runs sales. AI has to fit into that, not replace it.
You tried a chatbot. It didn't stick.
Because it couldn't see your data or do anything. An agent that reads and writes your systems is a different animal.
You want automation that touches real records.
Leads qualified, invoices matched, notes turned into fields. With approvals where money or customers are involved.
You don't want to hire a team for it.
Two senior engineers who embed for weeks beat a six-month hiring process and a 40-page recommendation.
What we integrate AI into
If it has an API, a database or a webhook, we can wire an agent into it. The usual suspects:
CRMs
Zoho CRM (our daily driver), HubSpot, Pipedrive, Salesforce. Lead triage, follow-ups, hygiene, handoffs.
ERP and accounting
Orders, inventory, invoices, purchasing. Read-only by default, approvals for writes, wrap before you migrate.
Support desks and inboxes
Tickets with full customer context, drafts for humans to approve, escalation rules that follow your playbook.
Databases and documents
Postgres, MySQL, Google Drive, Notion, SharePoint. Agents that answer from your data with citations, not vibes.
Billing and payments
Stripe, QuickBooks-style tools, your invoicing system. Always behind an approval step.
Your own web and mobile apps
We build those too. AI features wired into apps that already talk to your systems.
How an integration actually goes
The full process is on the process page. The short version:
- Day 0
We land.
Sit with your ops and sales teams, map every system including the spreadsheet, agree on what 'working' means with numbers.
- First weeks
One workflow, end to end.
The first agent goes live on a real workflow, scoped, logged, with approvals. You see it work before we widen anything.
- The build
The agent layer.
More workflows, more systems, dashboards people open, documentation humans can read. Weeks or months, depending on how much mess there is. We tell you which before we start.
- Handoff
We leave it running.
Monitoring, training, runbooks. Then we leave, or stay embedded. Your call.
Why not a chatbot vendor, a big agency or a freelancer?
| Chatbot vendor | Big agency | Freelancer | 2bros1ai | |
|---|---|---|---|---|
| Touches your real systems | Rarely | Eventually | Depends | From week one |
| Who does the work | Their support team | Whoever's on the bench | One person | The two people you met |
| Deliverable | A login | A deck, then a project | Code, maybe docs | Pull requests, docs, runbooks |
| How you pay | Per seat, forever | Hourly, open-ended | Hourly | Written scope and quote before we start |
| Guardrails | Their defaults | In the SOW appendix | Ask nicely | Scopes, logs, approvals by default |
Questions we get
- How much does AI integration cost?
- It depends on how many systems are involved and how much mess is in them. A two-system integration and a five-system agent layer are not the same job, so we don't publish a price list. Book the 30-minute call, tell us what you run, and you get a written scope and quote before anything starts.
- Can AI integrate with the software we already use?
- Almost always yes. If your system has an API, a database we can read, or even just webhooks and email, we can wire an agent to it. The exceptions are rare and we'll tell you in the first call.
- How long does it take?
- Honestly, it depends on the mess. A single workflow can be a matter of weeks; an agent layer across several systems is months. We scope it together on the first call and put the timeline in writing. What we do promise: you see something real running early, not a roadmap.
- Is our data safe with an LLM in the loop?
- Agents get scoped credentials, read-only access by default, an approval step before anything writes to a customer or money record, and full logs. We don't train models on your data. You can bring your own model provider keys.
- Do you work US hours? Can you come on-site?
- Both. We overlap daily with US Eastern business hours and work async the rest of the day with written updates. On-site is on the table too, anywhere; the first weeks in your office are often the best way to start. Where and for how long gets agreed on the call.
Related
Got a workflow like this to wire up?
Thirty minutes. We map one workflow live and tell you what it takes. No deck.