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Newtogen

AI-powered lead generation

Spend sales time on conversations that are likely to matter.

We build lead generation workflows that combine careful research, permitted data sources and AI-assisted qualification — so your team reaches the right organisations with relevant, respectful outreach.

The challenge

Where pipeline effort gets wasted

Sales teams often spend more time searching, sorting and updating records than speaking with potential customers.
  • Prospect lists are broad, outdated or poorly matched to your offer
  • Leads from different sources are not qualified consistently
  • CRM records are incomplete, duplicated or never updated
  • Generic outreach damages your reputation and response rates
  • No clear view of which channels produce good opportunities

Our approach

Responsible, research-led pipeline building

We define your ideal customer profile with your team, then build workflows that research and segment organisations using permitted data sources, score leads against agreed criteria and keep your CRM clean. AI assists with research summaries and personalised draft messages, but every outreach decision stays with a person. We do not build unauthorised scraping, unsolicited bulk messaging or anything that breaches platform terms or applicable regulations.

Capabilities

What Lead Generation includes

Prospect research

Research into organisations that match your ideal customer profile, using permitted sources.

Business segmentation

Grouping prospects by industry, size, needs and signals so messaging can be relevant.

Permitted data enrichment

Adding firmographic details from licensed or public sources in line with their terms.

Lead qualification

Consistent scoring of inbound and outbound leads against criteria agreed with sales.

CRM integration

Clean, de-duplicated records and automatic updates in your CRM.

Outreach workflow assistance

AI-drafted, personalised messages and follow-up reminders for review and sending by your team.

Human review

Approval steps before any contact is made, with opt-out handling built in.

Illustrative AI workflow

Example structure — not a live product demo

  1. Step 1: Business input

    Emails, documents, forms or tickets arrive as they do today.

  2. Step 2: AI processing

    Content is classified, extracted or summarised using your approved data.

  3. Step 3: Human review

    A team member checks, corrects or approves anything that matters.

  4. Step 4: Business output

    Approved results flow into your CRM, helpdesk or business systems.

Deliverables

What you receive

  • Ideal customer profile and segmentation model
  • Data source review (permissions and terms)
  • Lead scoring criteria and workflow
  • CRM configuration and integration
  • Outreach templates and review workflow
  • Pipeline reporting dashboard

Business benefits

Expected outcomes

Better-fit prospects

Effort concentrates on organisations most likely to benefit from your offer.

Consistent qualification

Every lead is assessed against the same criteria, regardless of source.

Cleaner CRM

Accurate records make forecasting and follow-up more reliable.

Protected reputation

Relevant, reviewed outreach respects recipients and your brand.

Illustrative use cases

How this can look in practice

Hypothetical scenarios that show typical applications. They are examples, not descriptions of specific client projects.
Example

Inbound lead scoring

Website enquiries are enriched with company information and scored so the sales team responds to the strongest matches first.

Example

Account research briefs

Before a sales call, a representative receives a concise research summary of the organisation, compiled from approved sources.

Example

Event follow-up workflow

Contacts who opted in at an event are imported, de-duplicated and assigned follow-up tasks with suggested message drafts.

Implementation process

How we deliver it

  1. Step 01

    Define

    Ideal customer profile, criteria and compliance boundaries.

  2. Step 02

    Source

    Identify permitted data sources and review their terms.

  3. Step 03

    Build

    Enrichment, scoring and CRM workflows.

  4. Step 04

    Review

    Human approval steps and opt-out handling.

  5. Step 05

    Launch

    Pilot with a small segment, then expand.

  6. Step 06

    Measure

    Track conversion by segment and refine criteria.

Relevant technologies

  • CRM platforms (HubSpot, Zoho, Salesforce)
  • Licensed data providers
  • Large language model APIs
  • Workflow automation
  • Python
  • Analytics dashboards

Technology choices are made per project, based on your requirements and existing systems.

FAQ

Lead Generation questions

Do you scrape websites or social networks for contact data?
No. We only use data sources whose terms permit the intended use, and we design workflows to respect data protection and anti-spam rules. Unauthorised scraping and unsolicited bulk messaging are outside our scope.
Does AI send messages automatically?
Not by default. AI drafts and suggests; your team reviews and decides what is sent. Automated sending, where appropriate, is limited to contacts with a lawful basis and includes opt-out handling.
Can this work with our existing CRM?
Usually, yes. We integrate with common CRMs through their APIs and adapt to your existing pipeline stages.

Lead generation workflows are designed to comply with platform terms and applicable data protection and electronic marketing rules. Specific legal requirements should be confirmed with your legal advisers.

Ready to talk about lead generation?

Tell us what you want to build, improve, or automate. Let's explore a practical solution together.