Automate sales proposal generation
Turn approved content and customer requirements into proposal drafts for your sales team.
A sales prospecting tool with a database of more than 200 million contacts, plus AI that researches accounts, writes emails, and analyzes calls.
Apollo AI is the set of AI features inside Apollo.io, a sales prospecting and engagement tool built around a database of more than 200 million contacts. Reps search for prospects in plain language, get outreach emails drafted in their own tone, and see AI-generated account summaries before a call. A built-in dialer and call recording tool analyzes conversations and produces summaries. A Chrome extension pulls contact data while browsing LinkedIn or a company website, and an MCP integration connects Apollo data to other AI tools. The AI features run on Google's Gemini models. Plans range from a free tier with limited monthly credits to paid tiers with more data export and automation limits, plus a custom enterprise tier.
This fits a sales or business development team doing its own prospecting that wants the contact database and outreach tools in one subscription rather than buying lists from a separate data vendor. A good starting point is the free or Basic tier for a small team, testing data quality and email deliverability before committing to a paid plan. As planning figures, the Basic tier runs about $49 per user per month, Professional about $79, and Organization about $119, billed annually, with monthly billing costing more; confirm current rates, since they change periodically. Watch two things: contact data accuracy varies by industry and region, as with most B2B databases, and export credit limits can run out faster than expected if a team pulls large lists out of Apollo instead of emailing from inside it.
Potential matches to review against your requirements. Explore matching tools or read a task guide before you choose.
Turn approved content and customer requirements into proposal drafts for your sales team.
Bring key business metrics together in dashboards and summaries for leadership.
Use historical trends and business data to plan for future customer demand.
Explore external sources to support business decisions.
The industries and leadership roles this tool is most often matched with.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $20.7K | $33.6K | $55.5K |
| Three-year total | $38.1K | $59.7K | $96K |
| First-year cost per unit | $1K | $1.7K | $2.8K |
| Average annual cost per unit (over three years) | $636 | $996 | $1.6K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $1.2K | $1.6K | $2.2K |
| Implementation | $5.4K | $9K | $15.3K |
| Integration | $3.9K | $7K | $12.6K |
| Staff time and change management | $3.5K | $5K | $7K |
| Security | $2.7K | $3.8K | $5.7K |
| Administration | $2.1K | $2.8K | $3.8K |
| Support | $975 | $1.3K | $1.8K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 20 enabled users. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of Apollo AI and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Export Apollo AI records, enrichment provenance, formulas, match rules, waterfalls, sequences, suppression data, and outcomes while keeping the CRM authoritative. Provider-specific data rights and automation chains may not transfer; revoke keys, stop sends, and confirm deletion before exit.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
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Where to check the product, price, security, and support.
Research observations recorded: 1. Evidence quality: Good support.
Recorded score and category rank across research updates.
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