Autonomous revenue infrastructure

Most sales teams can tell you who fits their ICP. PravRaha is built to tell you who is moving toward a purchase, why, and when.

PravRaha turns market signals into revenue intelligence: the accounts showing movement, the events behind it, the people who decide, and the action that follows.

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Drafts for your approval, sends from your own Gmail, Microsoft or SMTP accountSalesforce and HubSpot connectors

Real screens from the PravRaha GTM Controller, in 25 seconds: live buying signals matched to an ICP and scored for intent, what the agents found in a campaign, the buyers identified, and the six agents working through the campaign.

Teams working with PravRaha

The problem

Fit is not movement.

A territory of perfectly qualified accounts still gives a rep no idea which twenty to work on Monday. That list of who fits is sales intelligence. Adding another data source makes the visibility problem worse: more rows, the same uncertainty.

Traditional systems answer

Who fits?

Industry, size, region, stack. True on the day it was exported.

PravRaha is built to answer

Who is moving?

Which accounts changed, what changed, who decides, and what to do about it.

What it shows

Three questions, asked continuously.

PravRaha explains its method rather than claiming a hit rate. Every call carries the evidence that produced it.

Which accounts are showing movement?

Not every account that matches your filters. The ones where something changed: a leadership hire, a hiring surge, a funding round, a change in the stack.

Buying signals →

What explains the movement?

The business event stays attached to the account, so the reason is visible before anyone writes an email. A prediction without its evidence is a guess with a number on it.

Buyer intent →

When is attention worth spending?

Fit says an account could buy. Intent says it might. Timing is the judgment about when a conversation is likely to be welcome, from the recency and sequence of what happened.

Revenue timing →

The revenue intelligence loop

Signal to revenue, as one system.

Each stage hands something specific to the next, and the outcome re-scores the next cycle.

Intelligence Loop

7 stages · continuous

01
Signal
A change in the market: hiring, funding, leadership, tech stack, expansion.
02
Intelligence
The signal is attached to an account, a context and a likely business problem.
03
Prediction
Which accounts are moving toward a purchase, and how strongly.
04
Timing
How recently the event happened and what else happened around it, to judge where attention is worth spending.
05
Decision-maker
Who is in the buying committee: economic buyer, technical champion, internal coach.
06
Action
The next best action, drafted against the trigger that created it.
07
Revenue
Meetings, pipeline, and a feedback signal that re-scores the next cycle.

revenue → feedback → re-score → signal // every cycle makes the next one smarter

The product

Four screens from the working product.

Not a rendering. These are captures from the PravRaha GTM Controller, cropped and with personal data pixelated.

ICP Configuration in the PravRaha GTM Controller: employee range, funding stage, revenue stage, industries, geographies and decision-maker levels — The ICP is a stored model, not a paragraph in a doc. Employee range, funding stage, revenue band, industries, geographies and the decision-maker levels you sell to. The agents run against this.

Product-Context screen storing the product name, differentiation and named competitors used to ground outreach — Product context is captured once and reused: what you sell, how you differ, who you compete with. Messaging is grounded on this rather than on a template with a first name in it.

Campaign overview showing companies, buyers found and messages generated, with the AI response describing a limitation in the dataset — A real campaign mid-setup: 40 companies, 40 buyers, 240 messages drafted, nothing sent yet. Read the summary line at the top. The system reported that the dataset held no explicit software test or quality leaders instead of pretending the match was clean. That behaviour is the point.

Settings screen showing Salesforce and HubSpot integrations and connected Gmail and Microsoft sending accounts — Your own mailboxes. Gmail, Microsoft or SMTP, with a signature required before an account can send. Salesforce and HubSpot connect from the same screen. Email addresses are pixelated here; nothing else is altered.

See the full platform →

Revenue timing

The question most sales tooling skips.

Fit and intent are judgments about an account. Timing is a judgment about a moment. It is the difference between a conversation that lands and the same conversation a quarter late.

How timing is derived →

ICP fit

Tells you an account could buy.

Intent

Suggests an account may be interested.

Timing

Helps decide when attention is worth spending.

PravRaha reads the recency and sequence of events to suggest when conditions may be changing. It does not claim a validated buying date, and the site will not pretend otherwise.

From intelligence to action

The intelligence decides the action. Not the other way round.

Most tools start with a sequence and look for people to put in it. PravRaha starts with what changed at an account, and the action follows from that.

The trigger

The event that surfaced the account is what the first sentence of the message is about.

The committee

Economic buyer, technical evaluator and the person who lives with the problem get different threads.

The review

A person on your team reviews and approves each message before it is sent from your own mailbox, or on WhatsApp where it fits.

Why PravRaha

Three different questions.

Databases and intent providers are good at what they were built for. They answer a different question from this one.

A database

Who exists?

Contacts, firmographics, technographics. Necessary, and static the moment it is exported.

Intent data

Who may be interested?

Topic surges and site activity. Useful as confirmation, and sold to everyone in your category at the same time.

PravRaha

Who is moving, why, and when?

Business events attached to accounts, read together with fit and recency, and carried through to the action they imply.

Compare against specific tools →Read the manifesto →See use cases →

Stop treating every ICP account like an opportunity.

Point PravRaha at your market and see which accounts are moving, what moved them, and who to talk to.

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