> ## Documentation Index > Fetch the complete documentation index at: https://docs.parsalink.io/llms.txt > Use this file to discover all available pages before exploring further. # AI Agents > The CRM AI assistant is built from 16 specialized per-domain agents — one for contacts, one for opportunities, one for email, and so on — coordinated by a router.
PER-DOMAIN AGENTS

Instead of one giant assistant that knows everything, ParsaLink runs a fleet of small, focused agents. Each one owns a single CRM domain — and the right one is picked for you based on what you ask.

## Why Multiple Agents? A single all-knowing assistant has to load every tool, every example, and every instruction every time it answers — even when you're just asking it to mark a task complete. That's expensive (lots of LLM tokens), slow, and less accurate. ParsaLink routes each request through a small **classifier** first, identifies the right domain (contacts, opportunities, email, etc.), and then loads only that domain's tools and system prompt. You get faster, cheaper, more accurate responses. The agents share a common base prompt (formatting rules, response style, when to confirm vs. act) but each one has domain-specific knowledge layered on top. *** ## The 16 Domains | Agent | What it owns | | ------------------ | ------------------------------------------------------------------------------------ | | **contacts** | Search, create, update, bulk import, merge, duplicate checks for Contact records | | **accounts** | Same shape, for Account (company) records | | **opportunities** | Deal CRUD, stage moves, probability + amount updates, related contact/account lookup | | **cases** | Support case CRUD, priority + status transitions | | **tasks** | Task CRUD + reminders, due-date logic, automation-spawned tasks | | **email** | Drafting, sending, template creation/cloning, email-account routing | | **automations** | Building new automation rules from a natural-language description | | **meeting-notes** | Reading and writing meeting note attached to calendar events | | **tags** | Tag CRUD across all entity types, segmentation queries | | **comments** | Threaded comments on contacts, accounts, opportunities, cases, tasks | | **analytics** | Running ad-hoc analytics queries (generates safe Django ORM Python under the hood) | | **pipelines** | Pipeline + stage CRUD, opportunity pipeline configuration | | **communications** | Twilio call logs + SMS context lookup | | **calendar** | Booking events, comparing team availability, sending invites | | **web** | Web search for facts outside the CRM | | **shared-base** | Common ground rules every other agent inherits | The classifier may activate **multiple** namespaces for one message. Asking *"Show me all the qualified contacts at Globex with an open opportunity, and draft them an intro email"* loads `contacts`, `accounts`, `opportunities`, and `email` together. *** ## How the Router Decides The router classifier (`router-classifier` prompt template) takes your raw message and returns a JSON object like: ```json theme={null} { "intent": "send_intro_email", "namespaces": ["contacts", "email"], "confidence": 0.96, "reason": "User wants to email new contacts in a segment" } ``` The picked namespaces' tools and system prompts are then loaded for the actual answer. You'll usually see this happen invisibly. In some borderline cases the agent may ask a quick clarifying question if the classifier is unsure (e.g. *"Did you mean to update the contact or the opportunity?"*). *** ## Customizing the Agents (Admin) All 16 prompts live in **Admin → LLM → Prompt Templates** with `template_type = ai_agent`. They're versioned and audit-logged, so tuning the wording of a domain agent doesn't require a code deploy. Pick a template, edit the body, save. The change applies on the next message — no restart needed. Editing the **agent-shared-base** template affects every domain agent. Test changes on a non-production workspace first if you're making big structural edits. *** ## Adding Capabilities Each agent gets its set of tools from the matching directory under `packages/django/crm/ai_tools/` — `contacts.py`, `accounts.py`, etc. Adding a new capability to an agent is a code change (new function decorated with the tool registration). New tools are surfaced to the LLM automatically once the agent's namespace is loaded. If you have an idea for a capability that doesn't fit a domain — open a request and we'll figure out where it belongs. *** ## Reading the LLM Requests Every agent call lands in **Admin → LLM → Requests** with: which template was used, which model, the input message, the response, token counts, cost. Useful for: * Debugging when an agent answers wrong ("it should have used `update_task` but used `create_task`") * Spot-checking which namespaces were loaded for a borderline message * Measuring spend per domain (e.g. "the email agent is our biggest spender, time to tighten its prompt") *** ## What Each Agent Can Actually Do The table above is the elevator pitch. Below is what each agent can concretely accomplish when you ask it something — useful for picking which messages to send into chat (vs. doing it manually). ### contacts * *"Find John from Acme"* — search by partial name + company; disambiguation prompts when multiple match * *"Show me everyone tagged VIP who hasn't been emailed in 30 days"* — combined filter on tags + last activity * *"Create a contact for Sarah Smith, VP Marketing at Stitch, [sarah@stitch.io](mailto:sarah@stitch.io)"* — single-line create * *"Merge the two Globex Sarahs and keep the most recent email"* — duplicate cleanup * *"Bulk-update everyone in the prospect stage to source=Cold Outreach"* — mass field updates ### accounts * *"Find all accounts in the SaaS industry with >100 employees"* — combined firmographic filter * *"What's the latest activity on the Globex account?"* — timeline summary across linked contacts and opportunities * *"Show me accounts with no opportunity in the last 90 days"* — stale account triage ### opportunities * *"Show me deals closing this quarter"* — closing-window filter * *"Move the Globex deal to Negotiation and set probability to 70%"* — stage + probability update * *"What's the total amount of open opportunities by stage?"* — pipeline summary ### cases * *"Show me urgent cases that are still open"* — priority + status filter * *"Escalate this case to Andrew and tag it `vip-customer`"* — assign + tag in one step ### tasks * *"What's overdue for me?"* — personal overdue triage * *"Push everything on Amy's plate due Friday to next Monday"* — bulk reassign + reschedule * *"Create a task to follow up with the Globex contacts in 3 days"* — relative-date scheduling ### email * *"Draft an intro email to Sarah at Stitch about our marketing audit"* — AI compose grounded in workspace knowledge * *"Send the proposal email template to John Smith with the variable {amount} = \$12,500"* — template variable injection * *"Clone the Proposal Follow-Up template, rewrite it for cold outreach, save as v2"* — template authoring without leaving chat * *"Show me which template has the best open rate this month"* — per-template analytics ### automations (build via the `automation-builder` template) * *"Build a rule that sends a welcome email when a contact's source is set to Website, then creates a follow-up task in 3 days"* — describe the workflow in plain English, the agent assembles the trigger + steps and saves the rule * *"Show me which automation rule sent the most emails last week"* — analytics on rule firing ### calendar * *"Find a 45-minute slot for Andrew, Amy, and the Globex contacts next week, afternoons"* — multi-user availability intersection * *"Reschedule today's 3pm to tomorrow at 11am, keep the same attendees"* — single-line reschedule * *"Book a Teams meeting with John Smith tomorrow at 10am and send him the invite"* — provider-agnostic booking (Google Meet or Teams) ### meeting-notes * *"Save these notes on the Globex meeting and create a task to send the case study"* — paste raw notes, agent links them to the right event + extracts action items * *"Summarize what we discussed with Stitch last week"* — surfaces meeting notes filtered by account ### tags * *"Show me everyone tagged `enterprise` AND `interested`"* — combined tag filter * *"Create a `renewal-2027` tag and apply it to every customer with a contract expiring in 2027"* — bulk apply * *"What tags are most common on lost opportunities?"* — segmentation analytics ### comments * *"Add a comment to the Globex opportunity: 'They want the SOW by Friday'"* — quick note logging * *"Show me everything I've commented on this week"* — personal activity recap ### analytics * *"What's our average sales cycle by source?"* — see the [AI Analytics page](/ai/analytics) for the full set * *"Plot pipeline value by stage for the last 6 months"* — time series with chart ### pipelines * *"What stages are in the Enterprise opportunity pipeline?"* — pipeline + stage inspection * *"Add a new stage 'Security Review' between Negotiation and Closed Won"* — pipeline edit ### communications (Twilio) * *"Show me the call log with John Smith"* — call history retrieval * *"Send John an SMS: 'Heads up, sending the proposal in 5 minutes'"* — outbound SMS ### web (search-the-internet agent) * *"What's Globex's latest funding round?"* — public web search for facts outside the CRM * *"Find the LinkedIn profile of John Smith VP Sales at Stitch"* — researcher-style lookup that doesn't touch the CRM *** ## The Automation Builder A specific call-out because it's a power user move: the `automations` agent uses the `automation-builder` prompt template to translate natural language into a saved automation rule. Example: > *"When a contact's source changes to anything containing 'web', round-robin-assign them to the sales team, tag them `web-lead`, and send them a welcome email after 1 hour."* The agent: 1. Parses the trigger event (`contact_source_changed`) 2. Parses the trigger conditions (`source contains 'web'`) 3. Parses the sequence of actions (`round_robin_assign`, `add_tag`, `send_email` with a 1-hour delay) 4. Drafts the rule and shows it to you for review 5. Saves and activates on your confirmation You can iterate from there — the agent can edit the draft if you say "actually delay the email by 2 hours instead of 1" or "add another step that creates a follow-up task after 3 days." The automation builder won't activate a rule on the first try without your confirmation. You always get to eyeball the trigger + steps before they go live.