Sales automation
Sales automation is not 'send more emails faster'. It is matching the right action to the right pipeline stage at the right time, with enough personalisation that the message earns a reply. Done with cold-outreach SaaS tools, it produces volumes of templated emails that ruin sender reputation. Done with AI agents, it produces fewer but better messages, each grounded in the recipient's actual context.
The manual reality
Sales teams either spam (high volume, low quality, deliverability collapses) or hand-craft (low volume, high quality, doesn't scale). The middle path requires per-lead context, sequence intelligence (which message to send when, based on prior responses), and reply handling — three things that off-the-shelf sequencers do badly.
The WorkAist approach
The WorkAist sales agent runs the full outbound motion: enriches each lead (via the lead-enrichment agent), drafts personalised first-touch messages grounded in the recipient's context, sends from a warmed mailbox, watches replies, classifies each reply (interested / not interested / out of office / wrong person), routes interested replies to a human salesperson with full thread context, and continues sequences for non-responders. The sales rep handles meetings and closes; the agent handles everything before the meeting.
Implementation in 5 steps
- 1Connect your CRM (HubSpot, Salesforce, Pipedrive) and mailbox provider (Gmail, Outlook, IMAP).
- 2Define your ICP (ideal customer profile) and the source lists for prospecting.
- 3Pair with the lead-enrichment agent for per-lead context.
- 4Configure the sequence — number of touches, channel (email + LinkedIn), spacing, and exit criteria.
- 5Approve the first batch of drafts, let the agent send and handle replies, review interested leads in your inbox.
Connectors & agents involved
FAQ
Does this hurt deliverability or get classified as spam?▼
Volume and templated repetition are what triggers spam classification. The WorkAist agent sends fewer messages with more variation — each one different per recipient context — which is structurally less spam-like. Mailbox warm-up, IP reputation, and SPF/DKIM/DMARC alignment are handled by the platform. For high-volume outbound, the partner-outreach playbook (see docs/outreach.md) covers the full mailbox-fleet pattern.
What about reply classification — does it get it right?▼
Reply classification accuracy reaches ~95% on the common categories (interested, not interested, out of office, wrong person, unsubscribe). Edge cases (intent-unclear replies, multi-thread continuations) are routed to a human for triage. The classification model improves from your corrections.
Is this used for cold outreach or warm leads?▼
Both, with different settings. For cold outreach, sequence length is longer, personalisation density higher, exit on negative reply faster. For warm leads (inbound, content-driven), sequences are shorter, more direct, and route to a human sooner. Both flows use the same agent with different configurations.
How does it differ from Outreach.io or Salesloft?▼
Outreach and Salesloft are sequencers — they handle the cadence and templating well, but the per-lead personalisation is shallow (placeholder variables, not contextual prose). The WorkAist agent generates the message content fresh per lead with real context. The sequencing capability is comparable; the message-quality capability is structurally different.
Automate Sales automation this month
Open-source, self-hosted, AGPL-3.0. Your data stays in your infrastructure.
Get started