Support teams answering the same tickets all day
Half our queue is password resets and ‘Where’s my order?’
An agent drafts answers from your help center and order data, and hands the rest to a person.
AI agents & automation
AI agents that take repeat work off your team
Support, sales ops, and document work, tested on your real tickets before launch.
- Tested on your real tickets
- Human handoff built in
- Runs in your own accounts
30 minutes with a founder. Times show in your time zone.
AI agents & automation at a glance
AI agent development for support, sales ops, and document work: custom AI agents tested on your real tickets before launch, with a human handoff built in.
- Who it’s for
- Support teams answering the same tickets all day
- Founders adding AI to a product
- Ops teams retyping the same data
- What we build
- AI agents for customer support
- Sales and CRM automation
- Document and data extraction
- AI features inside your product
- Chat agents on your website, Slack, SMS, or WhatsApp
- Built with
- AI models from OpenAI, Anthropic, or Google
- Your help desk's API
- Python or TypeScript
- PostgreSQL with pgvector
- n8n for workflow automation
- What you own
- Code in your GitHub from day one
- Cloud and store accounts in your name
- IP assigned as each invoice is paid
How we'd build yours
Example plan
We don't have public case studies yet. Here's an example: a first support agent for a subscription software company on Zendesk.
- Pick the job
One job: first replies to billing and login tickets. We export past tickets with personal details removed, and your team scores the first drafts.
- Connect
We connect your help center and read-only billing data, then test it on questions like "Why was I charged twice?" for a test customer.
- Set the rules
What it must never promise, refund limits, and what goes straight to a person. You see the full test sheet, misses included.
- Shadow mode
It drafts inside Zendesk, and your team approves, edits, or rejects each reply. You see the approval rate.
- Improve
We fix the weak answers. You choose which ticket types it may send alone, if any.
- Launch
Launch on the approved ticket types, with a one-page guide for your team.
This is an example plan, not a past client project. Your plan depends on the jobs and systems involved.
Who this is for
Sound familiar?
Founders adding AI to a product
Customers expect AI. Which feature will actually work?
We pick one job AI does well, test it on your data, and ship it.
Ops teams retyping the same data
We retype invoices, POs, and form emails every day.
Rules run the routine steps, AI reads the messy documents, and a person approves what matters.
What we build
AI agents for customer support
A custom AI support agent works inside your help desk. It triages new tickets and drafts replies from your help center and order data. A person approves each draft until you decide what it may send alone. When it isn't sure, it hands off with a summary.
- Inbox triage by topic and urgency
- Drafted replies a person approves
- Order lookups, with handoff
Sales and CRM automation
The agent updates your CRM from forms, emails, and call notes, and drafts follow-ups for a rep to send. Plain rules run the routine steps. AI handles only steps that need judgment. That's where AI automation for small business should start.
- CRM updates from call notes
- Lead follow-up drafts
- Weekly pipeline summary in Slack
Document and data extraction
An agent does the first pass on invoices, purchase orders, and contracts, filling fields in your accounting system. Totals must add up and dates must make sense. Anything uncertain goes to a person, so bad data stays out of your books.
- Vendor invoices into your accounting system
- POs into your order system
- Key terms pulled from contracts
AI features inside your product
One AI feature in the product you already have, built in your repo behind a feature flag. A spending cap on your model account stops surprise bills.
- Search that answers plain questions
- Summaries of long notes or tickets
- Auto-tagging of new records
Chat agents on your website, Slack, SMS, or WhatsApp
The same agent answers in your site chat, Slack, SMS, or WhatsApp (official Business Platform), from one set of content and rules. It replies in the languages your customers use, tested on your real messages.
- Website chat from your help center
- Internal Q&A in Slack
- Order-status replies by SMS
How a project runs
Plain English at every step, and calls set around your working day.
How we start
We pick the first job, list what the agent must never do, and check that your tools connect. Before any code, we set up the repo, cloud, and model accounts in your name. Code lives in your GitHub from day one. IP is assigned to you as each invoice is paid.
Working together
You see a test sheet of every miss, not just the wins. AI drafts; a named engineer reviews every change, prompts included. We price by the project or the week, so faster work doesn't raise your bill.
A board you can open
Every miss becomes a card on the shared board. More in how we work.
Who you talk to
There's no account manager in between. Our team is in India, and we set call times around your working day.
Stack, and why
AI models from OpenAI, Anthropic, or Google
Picked per job on your test tickets. Billed to you, swappable later.
Your help desk's API
Works inside your current inbox.
Python or TypeScript
Mature AI libraries, easy to hire for.
PostgreSQL with pgvector
Answers come from your own content.
n8n for workflow automation
Visual workflows your team can read.
GitHub repository in your name
Code, prompts, and tests from commit one.
Cloud in your account
Billed to you. Nothing locked to us.
A shared Slack channel with our team
Questions and preview links in one place.
WhatsApp Business Platform (Cloud API)
Official API, on your own number.
Questions founders ask
Straight answers, including the ones about cost and time.
What is an AI agent?
An AI agent is software that uses a language model to read a request, decide the next step, and act in your tools: drafting a reply, updating a record, or handing off to a person. Unlike a simple chatbot, it works inside your systems, within limits you set.
What is the difference between an AI agent and a chatbot?
A chatbot mostly answers questions from a script or a knowledge base. An AI agent can also decide what to do next and take steps in your tools, such as looking up an order, drafting a reply for a person to approve, or updating a record. Either one can live on your website, in Slack, or on WhatsApp.
What is AI workflow automation?
It connects the steps of a routine job, such as reading a request, pulling the right data, drafting a response, and updating a system, and uses AI for the steps that need language understanding. A person stays in the loop wherever a mistake would be costly.
Should we use Intercom Fin or Zendesk AI instead?
Often, yes. If most answers live in your help center, their built-in agents set up fast and bill per resolution. Custom wins when the agent must act in your systems or follow rules a template can't hold. If built-in fits, we'll say so.
What if the AI gets it wrong?
A person can always step in. Before launch, we test it on your real past tickets and show you every miss, by ticket type. You decide which types it handles. It answers only from your content and hands off when unsure.
Can it take actions, like refunds or plan changes?
Yes, within limits you set. It can look up orders, change plans, or refund up to a dollar cap. The cap lives in code, not the prompt, so no customer can talk it higher. Anything above goes to a person.
Which tools can an AI agent connect to?
Agents commonly connect to helpdesks such as Zendesk or Intercom, CRMs such as HubSpot or Salesforce, Slack, email, and a company's own database or API. We confirm the exact connections while scoping, because every tool has its own access rules.
What does an AI agent cost, and how long does it take?
It depends on the job and the systems involved: how many tools it connects to, what it may do on its own, and how much testing your team wants before launch. Model usage is billed to your own accounts, and we estimate monthly model costs up front. On the call, you get a ballpark range. After scoping, you get a written estimate and plan.
Who owns the code and IP?
You do. Code lives in your GitHub from day one. IP is assigned to you as each invoice is paid, including prompts and test sets.
What hours do you work?
Our team is in India. We set call times around your working day, wherever you are, and questions go in a shared Slack channel.
Tell us the one job you want off your team's plate.
Or tell us which one sounds like you:
Or put it in writing
A few lines are enough to start, and nothing here commits you to anything.
- Tell us what you’re building.Who it’s for, what it needs to do, and any deadline you’re working to.
- A founder reads it.You get a reply by email, usually with a couple of questions.
- We talk for 30 minutes.You leave with a ballpark range, and a straight answer if we’re not the right fit.
Prefer email? sales.bydtech@gmail.com.
Send a briefGoes straight to the founders. No newsletter, no CRM sequence.