ProSalesMachine
Why ProSalesMachine

Any AI can write an email. Only one can prove why it works.

Generic chat assistants guess. ProSalesMachine collects verifiable evidence about a company first — website, tech stack, funding, hiring, news, CRM history — and only then writes the outreach. Every claim carries a source you can click.

Free plan · no credit card · EU-hosted

40+

Sourced facts per company

< 60 s

From company name to full playbook

95%

Statements backed by a citation

14

Interface and output languages

The gap between a chatbot and a sales system

It is not about who writes the nicer sentence. It is about who knows something the competition does not — and can prove it.

Source of truth

Training data of unknown age, plus whatever you paste in.

Live extraction from the company website, sub-pages, tech stack, DNS, funding and press — collected at the moment you ask.

Verifiability

Confident prose with no way to check it.

Every fact links to its source. Anything unsourced is marked as a data gap instead of invented.

Hallucination risk

High — the model fills gaps with plausible fiction.

Structurally reduced: the writing step may only use retrieved evidence, and the grounding rate is scored and shown.

Your context

You re-explain your product in every single chat.

Company profile, ICP, value props and winning messages are stored once and applied to every research automatically.

Scale

One prompt, one answer, manual copy-paste.

Bulk jobs process hundreds of accounts, score them and push the results into your CRM.

Prioritisation

No opinion on which account to call first.

Lead score from fit plus timing signals — with the reasoning and the evidence behind each point.

Freshness

Static answer, stale the day after.

Cached per source with a TTL, automatic re-runs and versioned evidence per account.

Team knowledge

Every rep starts from zero.

Shared workspace: profiles, playbooks and results are visible to the whole team, with role-based access.

Three layers of intelligence

Research, retrieval and real-time signals run as separate layers — so the output is not one model's opinion, but a chain of checkable steps.

Deep extraction

We crawl the site and its relevant sub-pages — product, pricing, careers, blog, imprint — and normalise what matters: positioning, segments, tech stack, locations, headcount signals, funding history.

Retrieval over your knowledge

Your documents, case studies, objection handling and past wins are embedded and retrieved for each account, so the messaging sounds like your company, not like a model.

Real-time signals

Hiring pushes, funding rounds, leadership changes, new tooling, press mentions and site changes become concrete reasons to reach out — dated and sourced.

Every feature, in one place

This is the full surface of the platform — not a teaser list.

Research & evidence

  • Company summary

    What they sell, to whom, how they position and where they are heading — condensed and sourced.

  • Pain point hypotheses

    Derived from real signals, each tied to the evidence that suggests it.

  • Buying signals

    Dated triggers — hiring, funding, launches, leadership moves, tech changes.

  • Evidence engine

    Collectors for site, DNS, tech stack, funding, news and firmographics, with fallbacks when a provider fails.

  • Citations everywhere

    Each statement is clickable back to its origin. No source, no claim.

  • Quality scorecard

    Evidence coverage, grounding rate and a grade from A to D for every analysis.

  • Data gap guidance

    Missing data is named, explained and paired with the source that would close it.

  • Source quality panel

    Per-source reliability, contribution and freshness, so you know what the answer rests on.

Outreach & coaching

  • Cold email

    Short, specific, built on one real trigger — not on adjectives.

  • LinkedIn message

    A version that fits the channel's length and tone, same evidence base.

  • Discovery questions

    Questions that only someone who did the research could ask.

  • Call opening script

    A first 20 seconds that earns the rest of the call.

  • AI sales copilot

    A threaded assistant with the full account context — ask, refine, rewrite, roleplay.

  • Objection coaching

    Likely objections plus answers grounded in your own proof points.

  • Magic sales mode

    One click turns raw account data into a complete, ready-to-send sequence.

  • Lead modes

    Cold, warm and existing-customer variants — the same account, three different conversations.

Scale & operations

  • Lead discovery

    Give us your product and site; we surface companies that match your ICP.

  • Bulk processing

    Hundreds of accounts per job, queued, retried and monitored.

  • Lead scoring

    Fit plus timing, explainable down to the individual signal.

  • CRM sync

    Push companies, contacts and research into HubSpot without copy-paste.

  • Evidence caching

    Per-domain and per-collector TTLs: repeat research is near-instant and stays consistent.

  • Scheduled refresh

    Evidence older than your threshold is re-collected automatically and versioned.

Trust, team & platform

  • Company profile

    ICP, value props and tone stored once, applied everywhere.

  • Knowledge base

    Your material becomes the substance of every message.

  • Workspaces & roles

    Multi-tenant organisations with row-level isolation between teams.

  • 14 languages

    Interface and generated sales copy, including full right-to-left support for Arabic.

  • Monitoring & logs

    Collector telemetry, latency and health — visible, not hidden.

  • Plans & billing

    Transparent plans, server-side entitlement checks, no silent upgrades.

What happens in those 60 seconds

Four steps, each one auditable.

  1. You enter company, website and what you sell.

  2. Collectors gather evidence in parallel and de-duplicate it.

  3. Retrieval adds your knowledge, ICP and winning language.

  4. The playbook is written — with citations, score and open gaps.

The honest objections

The questions serious buyers ask before they trust a tool like this.

Can I not just do this with a chat assistant?

You can produce text, yes. What you cannot produce is dated, sourced evidence about a specific company, a stored profile of your own offer, a score that ranks 300 accounts, and a CRM record at the end. That chain is the product.

How do you avoid invented facts?

The writing step is only allowed to use retrieved evidence. Anything not covered becomes an explicit data gap with a suggestion for the source that would close it, and every analysis reports its grounding rate.

What if a data provider is down?

Collectors fail independently. If one returns an error or times out, fallback sources fill in and the scorecard shows exactly which parts of the picture are thinner.

Does it sound like a robot?

It sounds like your best rep, because it is fed your own case studies, proof points and phrasing — and the copilot lets you rewrite any passage in seconds.

Is it usable outside German and English?

Yes. Fourteen languages for both the interface and the generated sales copy, including right-to-left layout for Arabic.

How fast is the team productive?

One profile setup, then every research inherits it. Most teams run their first sourced playbook within minutes of signing up.

Stop guessing. Start proving.

Run one account through it and compare the result to whatever you use today. That comparison is the whole pitch.

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