Sales demand outside business hours
Prospects arrive through the website when the team is unavailable, and a delayed first response lowers the chance of continuing the conversation.
AI sales agents
A website conversation can become a sales-ready opportunity.
We build RAG agents that retrieve approved knowledge, qualify needs, update the CRM and hand full context to sales.
Request diagnosis — $150What is slowing the operation down
Leads unanswered after hours
Repeated technical questions
Captured data that never reaches sales
What changes with a connected system
24/7 response and qualification
Answers grounded in controlled knowledge
Complete CRM and sales-team handoff
Who it is for
Immediate assistance when a sale needs context, not a generic answer.
A sales AI agent creates value when questions repeat, approved knowledge exists, and the team must distinguish a serious opportunity before investing human time.
Technical or extensive product lines
The first conversation requires product sheets, policies, applications, or FAQs without improvising information the company has not approved.
Teams receiving incomplete leads
Sales needs company, requirement, urgency, and context before outreach but currently gets isolated forms or conversations that are hard to reconstruct.
Connected processes
From the first question to a traceable opportunity.
The agent works within defined boundaries: it retrieves approved sources, captures necessary data, records what happened, and hands off when human judgment is needed.
- Website and forms
- RAG knowledge base
- CRM and pipeline
- Email or messaging alerts
- Conversation analytics
Core capabilities
Sales AI with sources, rules, and a human handoff.
Grounded answers
RAG retrieval limits answers to approved content and can record the source supporting information presented to a prospect.
Conversational qualification
Natural questions collect company, requirement, application, timing, and contact data without turning the exchange into a rigid form.
CRM updates
The agent creates or completes the opportunity, summarizes the conversation, and preserves structured fields for follow-up and measurement.
Context-rich handoff
When it detects intent, risk, or an out-of-scope question, it alerts sales with history, evidence, and a suggested next step.
Implementation
Three stages to launch a controlled AI agent.
We test answer quality and boundaries before allowing actions in sales systems.
Goal and knowledge
We define users, intent, questions, valid sources, restricted topics, qualification criteria, and the moments that require human intervention.
Agent and evaluation
We build conversation and RAG retrieval, prepare test scenarios, and measure accuracy, coverage, abstentions, and summary quality.
Integration and monitoring
We connect CRM and alerts with least privilege, observe real conversations, and document content review, incidents, and future improvements.
Related real case
Laura · RAG sales agent
Documented real case: conversation, knowledge retrieval, qualification, CRM update and sales notification.
View full case studyFrequently asked questions
Before implementing an AI sales agent.
Can the agent make up an answer?
No model removes that risk completely. We reduce it with approved sources, instructions, boundaries, abstention behavior, testing, and conversation review based on criticality.
Does it replace the sales team?
No. It handles availability, repeated questions, capture, and initial qualification. Salespeople retain decisions, negotiation, and conversations requiring judgment or a human relationship.
Can it update our CRM automatically?
Yes, with defined permissions and fields. We start with limited actions, validate duplicate handling, and preserve traceability before enabling broader automation.
How does the knowledge stay current?
We define content owners and a review schedule. Updates, ongoing evaluation, and monthly monitoring can be purchased as a separate, optional service.
Start with the process costing you the most time.
The $150 diagnosis identifies three priorities, estimates impact and defines the implementation path. If you move forward with OrbiLabs, the full $150 is deducted from the project.
Request diagnosis — $150