AI SDR and Sales Agents
Agents that research an account properly, write something a person would actually reply to, respect deliverability and consent rules, and hand a warm conversation to your team before they can do any damage.
The failure mode of an AI sales agent is not that it does not work. It is that it works at volume, in your name, and the damage is measured in domain reputation and in prospects who now associate your brand with generic mail. Every design decision in this engagement is aimed at that risk.
An AI SDR agent researches accounts and contacts, drafts and sends outbound messages personalised on genuine findings, handles replies within a defined boundary, updates the CRM, and hands qualified conversations to a person, operating within consent, deliverability and brand rules enforced by the system rather than by instruction.
What actually determines whether this works
- Deliverability, before anything else. Authentication, domain and inbox warming, volume ramps, engagement-based throttling and suppression discipline. An agent that gets your domain filtered has cost you far more than it could ever earn.
- Research quality, not template variables. Personalisation that references something real and specific beats a merge field every time, and readers can tell the difference immediately.
- Consent and jurisdiction. Different rules apply by region and by contact type. Those rules belong in the system as enforced constraints, not in a training note.
- A bounded reply behaviour. The agent may clarify, schedule and answer defined questions. Anything about price, terms, security or a complaint goes to a person immediately.
- Honest measurement. Meetings held and pipeline created, not opens and clicks, which move for reasons unrelated to whether the message was any good.
How we build a sales agent
Define the boundary first
Before any message is drafted we agree, in writing, what the agent may say, what it must never say, which claims it is permitted to make, and what triggers immediate human handover. Pricing, contractual terms, security assurances, competitor comparisons and anything resembling a complaint are out of scope by default.
Research before writing
The agent gathers real signals about the account, and where it finds nothing specific, it says so internally and the contact is skipped rather than receiving a generic message. Skipping is a feature: sending nothing is always better than sending something that reads as automated.
Write in your voice, within your claims
Message generation is constrained to your approved positioning and claim set, reviewed by your team during the build, and scored against examples of what good looks like from your best performers. Drafts are checked against a prohibited-claims list before sending.
Enforce deliverability in the system
Authentication configured properly, volume ramped gradually, sending throttled per domain, suppression lists respected absolutely, and engagement monitored so a falling reply rate reduces volume automatically rather than continuing until something breaks.
Hand over warm, with context
When a prospect engages meaningfully, the agent stops and hands to a named person with the full thread, the research it used and a suggested next step, and the CRM is updated in the same action. The value is a person joining a live conversation, not a lead score in a queue.
Reply quality is the only metric that matters early
Open rates are unreliable and click rates are easy to inflate. We measure positive reply rate and meetings held from the first week, because those are the only numbers that distinguish outbound that works from outbound that quietly damages your domain.
Compliance is not optional
Outbound is regulated, and the rules differ by jurisdiction and by whether the contact is a business or an individual. We build the constraints into the system rather than into a policy document:
- Lawful basis and consent recorded per contact, with region-specific rules applied automatically.
- Identification of the sender and a working, honoured unsubscribe in every message.
- Suppression lists applied at send time, including across campaigns and domains.
- Retention and deletion of prospect data to your policy, with deletion requests handled properly.
- An audit record of what was sent to whom, when, and on what basis.
Where a business case is needed for the programme as a whole, AI ROI analysis covers it on your own numbers rather than on vendor benchmarks.
How the engagement runs
Deliverability and boundaries are established before a single message goes out.
Boundary, claims and compliance
What the agent may and may not say agreed in writing, consent and jurisdiction rules mapped, prohibited claims listed.
Deliverability foundation
Authentication, domain and inbox setup, warming schedule, throttling and suppression configured before volume.
Research and drafting
Signal gathering, personalisation, message generation constrained to approved positioning, reviewed against your best performers.
Reply handling and handover
Bounded reply behaviour, escalation triggers, CRM updates and warm handover with context.
Ramp and handover
Graduated volume increase with reply quality monitored weekly, then handover of the system and the operating playbook.
What you receive
An outbound system your brand can survive, with the controls that keep it that way.
Sales agent
Research, drafting, sending, reply handling and CRM updates, deployed as infrastructure as code.
Boundary and claims policy
What the agent may say, what it must never say, and what triggers handover, enforced in the system.
Deliverability setup
Authentication, warming, throttling, suppression and engagement-based volume control.
Compliance controls
Consent and jurisdiction rules, unsubscribe handling, retention and the audit record.
Message quality evaluation
Drafts scored against your best performers and the prohibited-claims list, as a release gate.
Performance dashboard
Positive reply rate, meetings held and pipeline created, with deliverability health alongside.
Is this the right engagement?
Worth being direct. AI SDR and Sales Agents is the wrong spend in some situations, and those are listed rather than buried.
Good fit if
- Outbound is already a real channel and the constraint is research and drafting time.
- Your positioning and claim set are clear enough to be written down.
- A person will take over every conversation that becomes genuinely interested.
- You can accept a slow volume ramp for deliverability reasons.
- Success is measured in meetings and pipeline rather than in messages sent.
Choose something else if
- The goal is maximum volume at minimum cost. That will damage your domain and your brand.
- Nobody can articulate the positioning or approve the claim set.
- There is no capacity to handle the replies the agent generates.
- Your market is small and high-value, where a person writing twenty considered messages will beat this.
Frequently asked questions
Marked up with FAQPage schema so these answers can surface directly in search results and inside AI assistant responses.
What does an AI SDR agent actually do?
It researches accounts and contacts for genuine signals, drafts and sends personalised outbound within an approved claim set, handles replies inside a defined boundary, updates the CRM, and hands any conversation that becomes meaningful to a named person with full context.
Will this damage our domain reputation?
It will if deliverability is treated as an afterthought, which is the most common failure in this category. We configure authentication, warm domains and inboxes gradually, throttle per domain, honour suppression absolutely and reduce volume automatically when engagement falls.
How personalised can the messages really be?
As personalised as the signals available, which is why the agent skips contacts where it finds nothing specific. A merge field is not personalisation and readers know it. Sending fewer, genuinely researched messages consistently outperforms sending more generic ones.
Where does the agent stop and a person take over?
At the first sign of real interest, and immediately on anything about pricing, terms, security or a complaint. The handover carries the full thread, the research used and a suggested next step, so the person joins a conversation rather than starting one.
How do you measure whether it is working?
Positive reply rate, meetings held and pipeline created, alongside deliverability health. Opens and clicks are reported but not optimised for, because they move for reasons that have little to do with whether the message was worth reading.
Often paired with this
Most clients combine two or three engagements from the AI Agents & Agentic Automation pillar. These are the ones that most often run immediately before or after.
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Read more →AgentOps: Monitoring, Evaluation and Guardrails
The operations layer for production agents: trajectory tracing, evaluation, spend ceilings and a tested kill switch.
Read more →Is this the right engagement?
Tell us what you are trying to build. If a different service fits better, or if you do not need us at all, we will say so.