AI SDR Agent

An AI SDR agent finds companies matching your ideal customer profile, researches each one properly, and writes an opening message that proves someone looked. It does the volume work of three junior SDRs without producing the generic output that gets three junior SDRs ignored.

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Who it's for

B2B teams doing outbound.

What changes

A full pipeline of researched prospects without hiring three SDRs.

Starting at: ₹75,000
Timeline: 3–5 weeks
Category: AI Sales Agents
Built from: Vashi, Navi Mumbai

Key takeaways

The list is 80% of outbound performance. The script is closer to 10%.
Research depth is what separates this from mail-merge, and it is the expensive part.
Start in approve-before-send mode; move to automatic only once you trust the output.
Builds in 3–5 weeks from ₹75,000; running cost scales with research volume.
Useless without a clearly defined ideal customer profile — that work is yours, not ours.

What an SDR actually spends their day on

Watch a junior SDR for a week and the split is roughly: two hours finding companies, three hours researching them badly, two hours writing near-identical emails, and forty minutes actually in conversation.

The forty minutes is the job. Everything else is preparation that has to happen and that nobody enjoys, which is why it gets done at declining quality as the day goes on.

The agent takes the preparation. It does not replace the conversation, and any supplier telling you it does has not watched a real sales team work.

Defining the ICP is your job, not ours

This is where these projects succeed or waste money, and it happens before any code is written.

A usable ideal customer profile is not "SMBs in Maharashtra". It is a set of observable signals: company size band, industry, whether they run a particular system, whether they have a specific role on staff, whether they recently did something that creates the need you solve.

We run a session to extract this from your closed-won deals rather than your opinions, because the two are frequently different. Businesses routinely discover that the segment they think is their core market has the worst close rate.

How deep the research goes

Depth costs money, so it is a dial rather than a setting. What each level buys you:

Level	What it gathers	Cost per prospect	Use when
Basic	Firmographics, website summary	Lowest	High-volume, low-value pipeline
Standard	Plus role, recent news, tech signals	Moderate	Most B2B outbound
Deep	Plus job postings, filings, competitor moves	Higher	High-value, small target list
Named account	Everything, plus a written account brief	Highest	Strategic accounts only

For a ₹6-lakh engagement, deep research on 40 companies beats basic research on 4,000. For a ₹45,000 chatbot build, the reverse. We set the dial against your average deal size rather than defaulting to maximum.

Approve before send, at least at first

Every deployment starts with the agent drafting and a human approving. Your salesperson sees a queue of researched prospects with a drafted opener and approves, edits or rejects each one.

Two things happen in the first fortnight. You find out how good the research actually is, and the rejections become training signal for what to change. Most clients move top-of-funnel to automatic after three or four weeks and keep approval on their higher-value segments permanently.

Going straight to fully automatic on day one is how businesses end up sending something embarrassing to a company they were already in conversation with.

Suppression is not optional

The fastest way to look incompetent is to cold-approach a current customer, an active opportunity, or someone a colleague emailed last week.

The agent checks against your CRM before every send: existing customers, open opportunities, anyone contacted in the last 90 days, anyone who asked not to be contacted, and any domain on your exclusion list. This is unglamorous plumbing and it is the difference between a system your sales team trusts and one they quietly turn off.

What to measure

Not emails sent. Sent volume is the vanity metric of outbound and optimising for it degrades everything else.

Measure reply rate, positive reply rate, and meetings booked per hundred researched. Then measure the same numbers split by ICP segment, because the useful discovery is almost always that one segment works twice as well as the others and deserves the whole budget.

What is operating at the end

A configured agent with your ICP, prospect sourcing, research at your chosen depth, drafted openers, an approval queue, CRM suppression checks, automatic logging of every touch, and segment-level reporting on replies and meetings booked.

FAQ

AI SDR Agent — your questions

Where does it source prospects from?

Wherever you have legitimate access — your existing CRM and lists, enrichment providers you subscribe to, public company data, and industry directories. We do not scrape platforms in breach of their terms, because the risk lands on your domain and your accounts rather than ours.

Can it replace our SDR team?

It replaces the research and drafting portion of their work, which is most of their hours and none of their value. Teams that keep the humans and give them the agent's output book substantially more meetings than teams that cut headcount and run it unattended.

How is this different from the cold email personalisation agent?

This one finds and researches prospects and then writes. That one takes a list you already have and does the personalisation and sending infrastructure. If you have no list, start here. If you have a list and poor reply rates, start there.

What if our ICP is not well defined?

Then that is the first phase of the project, and we will say so at quoting. We derive it from your closed-won and closed-lost data rather than from a workshop, because what actually converts is usually narrower and stranger than what a team believes converts.

Want a AI SDR Agent for your business?

Tell us what the process looks like today and we'll tell you what it would look like automated — and what it would cost.

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