Agentic AI System for Quotation SLA Monitoring: Automated Quotation Intelligence

Key facts at a glance

Project facts & technologies

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Project name: Agentic AI System for Quotation SLA Monitoring — Automated Quotation Intelligence
Industry: B2B Sales, Commercial Operations, Cross-Industry
Use case: Autonomous quotation email triage, SLA tracking, AI-drafted responses, manager escalation
Core technology: n8n workflow orchestration, LLMs for classification and drafting, PostgreSQL state store
Integrations: Gmail API, Outlook / Microsoft 365 API, sales shared mailboxes
SLA tiers: 6 hours first response · 12 hours follow-up · 24 hours manager escalation
Agent behaviors: Email triage, intent classification, customer matching, SKU extraction, priority, drafting, follow-up, escalation, reporting
Human-in-the-loop: Salesperson reviews and approves every LLM-drafted quotation before send
Manager outputs: Live SLA dashboard, salesperson scorecards, performance summaries, quote-to-win analytics
Stakeholder users: Sales reps, sales managers, commercial leadership, audit & compliance
SLA outcome: 95% SLA compliance across quotation channels
Speed outcome: 50% reduction in quotation response time
Governance: Role-based access control (RBAC), full audit log, tamper-evident records
Deployment: Cloud-native, encrypted in transit, integrates with existing sales mailboxes

About the industry

Why are quotation SLAs such a hard operating problem for B2B sales?

In every B2B sales operation, the quotation cycle is the single most important commercial workflow — and the most leaky. A customer sends an email asking for a quote on a specific product, configuration, or service. From that moment, every minute of delay erodes two things: the probability that the customer buys from you, and the probability that they trust you to deliver. The faster the quote, the higher the conversion, the higher the customer satisfaction, the more credible the brand. And yet, in most B2B operations, the quote takes far too long.

The reasons are structural, not personal. Sales reps live in inboxes that receive dozens of internal and external emails per day; a quotation request is one stream among many. Managers don't know a quote was even requested until someone surfaces it. And the SLAs themselves are often informal — never quantified, never tracked, never escalated. Agentic AI changes the economics by autonomously monitoring inbound email, classifying quotation requests in seconds, opening explicit SLA timers, drafting responses for human review, and reporting on performance in real time.

The challenge

What problem does the Agentic AI System solve?

AiSPRY's commercial client needed to turn quotation handling from a reactive, inbox-dependent practice into a governed, AI-augmented workflow. Several structural challenges had to be solved together.

Key challenges

Quote requests buried in busy inboxes — salespeople receive dozens of emails a day; a quotation request often sits unseen for hours before anyone acts on it.
Informal, untracked SLAs — quote turnaround expectations are stated but not tracked; nobody knows whether a quote is late until it has already cost the deal.
No manager visibility until breach — by the time a manager learns a quote is overdue, the customer has often already moved on; escalation is reactive, not preventive.
Manual drafting overhead — every quotation email is typed from scratch, even when 80% of the response is the same product / pricing context the rep wrote yesterday.
Slow response erodes conversion — B2B conversion is directly correlated with quotation speed; every additional hour reduces close probability.
Cross-mailbox fragmentation and no audit trail — quotation requests arrive across Gmail and Outlook, shared inboxes, and personal addresses; nothing unifies the view and there is no continuous record of who responded when.

The solution

How does the Agentic AI System work?

AiSPRY built an autonomous AI agent that owns the entire quotation triage and SLA workflow. The agent continuously monitors inbound email channels, identifies quotation requests using an LLM-based intent classifier, opens explicit SLA timers, drafts tone- and brand-aligned responses with LLMs, escalates delays to managers, and produces real-time performance summaries — orchestrated on n8n with RBAC and full audit.

Email triage and SLA tracking

Autonomous email triage — Gmail and Outlook monitoring, intent classification, customer and contact matching, product / SKU extraction, priority scoring, and auto-routing to the right sales owner
SLA tracking and escalation — 6h first-response, 12h follow-up, and 24h manager escalation timers persisted in PostgreSQL, with live breach alerts and tier-aware urgency cues

AI drafting, manager console, and governance

AI-assisted quotation drafting — tone- and brand-aligned LLM drafts with inline product and price lookups, clarifying questions where ambiguous, and follow-up nudges as SLA tiers advance
Salesperson-in-the-loop — every draft reviewed, edited, and approve-and-sent from the rep's own inbox; the AI assists, the human owns the customer relationship
Manager console and reporting — live SLA dashboard, salesperson scorecards, performance summaries, and quote-to-win analytics
Governance and audit — RBAC across sales, management, and audit; tamper-evident audit log of every agent action

Video demo

See the quotation SLA agent in action

A walkthrough of the Agentic AI System for Quotation SLA Monitoring — autonomous Gmail and Outlook triage, LLM-drafted quotations landing in the rep's inbox for approve-and-send, the 6h / 12h / 24h SLA timers running in PostgreSQL, and the live manager dashboard with breach alerts and scorecards.

Agentic AI for quotation SLA — orchestrated, audited, AI-drafted

Click to play · n8n + LLMs + PostgreSQL + Gmail / Outlook APIs

<strong>Demo.</strong> Live walkthrough of the Agentic AI System for Quotation SLA Monitoring — autonomous mailbox triage, 6h / 12h / 24h SLA timers, LLM-drafted quotation emails, manager escalation, and audit-grade governance.

Autonomous triage — quote intent classifier, customer matching, and SKU extraction in seconds
Governed SLA timers — 6h / 12h / 24h tiers persisted in PostgreSQL with tier-aware nudges
LLM-assisted drafting — tone- and brand-aligned drafts ready for approve-and-send from the rep's inbox
Manager console — live SLA dashboard, scorecards, and quote-to-win analytics with RBAC and audit

Solution architecture

What does the Agentic AI architecture look like?

The platform follows a five-stage agentic pipeline that takes inbound customer email and converts it into a fully tracked, SLA-governed, AI-drafted, manager-visible quotation workflow. Email channels (Gmail and Outlook) feed the agent's inbox triage on n8n, an LLM intent classifier routes requests, a PostgreSQL state store tracks SLA timers and fires manager escalations, LLM drafting lands quotations in salesperson inboxes for approve-and-send, and a manager console with RBAC and audit exposes SLA breach status, scorecards, and quote-to-win analytics.

Agentic AI System for Quotation SLA Monitoring architecture — email channels, n8n agent inbox triage, PostgreSQL SLA tracker and escalation, LLM drafting and decision, and manager console with RBAC and audit — <strong>Figure 1.</strong> Agentic AI System for Quotation SLA Monitoring architecture — email channels → agent inbox triage (n8n + LLM) → SLA tracker & escalation (PostgreSQL) → LLM drafting & decision → manager console & audit.

Designed around constraints

How does the platform handle salesperson trust, SLA governance, and audit?

Building an agentic AI system that operates on live customer email and represents the organization to customers imposes constraints that an ordinary automation script cannot meet. AiSPRY engineered around four.

Salesperson-in-the-loop, always

Every LLM-drafted quotation is reviewed and approved by a human before send
The rep owns the customer relationship — the AI assists, it doesn't replace
Replies are sent from the rep's own inbox to preserve continuity for the customer
Escalations route through managers, not around them

SLA-governed and built on n8n

Every quotation request gets an explicit SLA timer the moment it is identified
Tier-aware nudges keep salespeople ahead of breaches, not behind them
Manager escalation fires automatically as breaches approach — no surprise overdues
Workflow orchestration on n8n means every step is visible, editable, and auditable

Governance and audit by design

Role-based access control separates sales, management, and audit roles
Full audit log of every agent action — triage, draft, escalate, send, report
Tamper-evident records of customer-facing replies and manager escalations
Encrypted in transit between mailbox APIs, agent, state store, and dashboards

Impact & outcomes

What measurable results does the Agentic AI System deliver?

The platform was engineered against two headline metrics — SLA compliance and response time — both moved sharply in the right direction. Beyond those, the system also shifts the operating practice of B2B quotation handling from reactive and manual to governed and AI-augmented.

SLA compliance and response speed

95% SLA compliance across quotation channels — measured, not estimated
50% reduction in quotation response time versus the manual baseline
Every quotation request opens a tracked SLA timer the moment it is identified
Tier-aware nudges keep salespeople ahead of breaches

Customer experience and conversion

Faster responses translate directly into higher customer satisfaction
Higher quote-to-win conversion through faster, on-brand replies
Tone- and brand-aligned drafting produces a consistent customer experience
Customer relationship continuity preserved through send-from-rep-inbox design

Sales productivity and governance

Significant reduction in manual inbox triage burden across sales reps
Salespeople spend less time typing and more time selling
Better SLA governance through live dashboards and scorecards
Full audit log of every agent action supports commercial governance

Frequently asked questions

Quotation SLA Agent — frequently asked questions

Below are the most common questions about how the agent works, what it does autonomously, where the human stays in control, and how it is deployed across a B2B sales operation.

What is the Agentic AI System for Quotation SLA Monitoring?

It is an autonomous quotation intelligence platform built by AiSPRY for B2B sales and commercial operations teams. The agent continuously monitors Gmail and Outlook mailboxes to identify quotation requests, opens explicit SLA timers (6h / 12h / 24h) on each one, drafts quotation emails using LLMs for salesperson review, auto-escalates delays to managers, and produces real-time performance summaries. Built on n8n, LLMs, PostgreSQL, RBAC and audit logs, and Gmail / Outlook APIs.

What problem does it solve for a sales operation?

Two structural problems erode B2B quotation performance: quotation requests buried in busy inboxes, and informal SLAs that nobody is actually tracking until they have already been breached. The agent solves both — detecting quote requests in seconds, opening explicit governed timers, escalating delays to managers proactively, and assisting salespeople with LLM-drafted responses. The result is 95% SLA compliance and a 50% reduction in response time.

How do the 6h / 12h / 24h SLA tiers work?

The moment the agent identifies an inbound quotation request, it opens an explicit SLA record in the PostgreSQL state store. A 6-hour first-response timer starts immediately — the rep is expected to send a substantive reply within that window. At 12 hours, the agent fires a follow-up nudge if the rep has not yet responded. At 24 hours, the agent auto-escalates to the assigned manager with full context. SLA tiers are configurable per customer segment and account type.

Does the AI send emails directly to customers?

No — the salesperson stays in the loop on every customer-facing reply. The agent drafts the quotation email and lands it in the rep's own inbox ready for review, edit, and approve-and-send. The actual email is sent from the rep's own account, preserving continuity for the customer. The agent's role is to remove the drudgery of drafting from scratch and inbox triage — not to replace the relationship between the rep and the customer.

What measurable results has the system delivered?

Two headline metrics. The platform delivers 95% SLA compliance across quotation channels — measured continuously against the 6h / 12h / 24h tiers, not estimated from quarterly reports. And it delivers a 50% reduction in quotation response time versus the manual baseline. Beyond the headline numbers, the system has driven significant reductions in manual inbox-triage burden, higher quote-to-win conversion through faster on-brand replies, and better SLA governance across the commercial organization.