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AI assistant for amoCRM: leads, deals, and conversations
We connect an AI assistant to amoCRM: it reads leads and conversations, qualifies requests, updates the card and task once, and hands the manager a transcript, a reason, and the next step.
The assistant moves a lead through the amoCRM pipeline, keeps deal context, and hands the dialog to a manager with a transcript.
Pricing
from ₽600,000
per project
This is the lower bound of a project. We scope the exact quote after a brief: it depends on volume and the number of integrations.
Capabilities
Lead and deal context
The assistant pulls the conversation history, deal stage, amount, owner, and past tasks from amoCRM. Context comes from fields and notes, so the conversation starts from facts.
Qualification and follow-up
The assistant asks questions from your script, records budget, timeline, role, and interest, then sends a follow-up in chat or email. Every answer lands in the lead fields.
One card and one task
The outcome is written to amoCRM once: the assistant adds a note, moves the stage, and creates a task. Chat and call stay on one deal.
Handoff with context
On escalation the manager gets the transcript, the reason for handoff, and the next step. The dialog continues from the point where the customer stopped.
From request to result
1
Pipeline audit
We review the pipelines, stages, and required fields. We mark where the assistant reads a lead, which fields it changes, and when it hands the dialog to a manager.
2
Data and permission model
We describe how amoCRM entities map onto the assistant schema, the lead dedup rule, and the technical account rights. We fix the fields open for reading and writing.
3
Integration and scenarios
We connect the amoCRM API and webhooks, build qualification, follow-up, and handoff scenarios. Each scenario runs on a test pipeline before launch.
4
Pilot and launch
For two weeks the assistant works on real leads in a limited pipeline. We measure qualified requests, tasks, and card edits, then move the scenarios to production from week four.
Check if it fits you
Good fit
amoCRM with an API and webhooks
The assistant connects to your pipeline directly: it reads leads and deals, receives stage-change events, and writes the result to the card.
A sales process with an owner
The pipeline has an owner who sets the stages and required fields. The process owner approves the qualification rules and signs off on the pilot.
Not a fit
A CRM without an API
If the cards live in spreadsheets or a custom database without an API, data migration comes first. The assistant connects after the move.
Automatic discounts and money decisions
A manager confirms discounts, refunds, and write-offs. The assistant collects arguments and prepares the calculation, while the money decision stays with a person.
What you get
−70%
time spent handling a request
In the retail-support-bot case the assistant pulled the order and customer history from the CRM before the first reply and created a manager task on disputed amounts. 82% of requests closed without an operator.
2
Pipelines in the base scope
The base delivery covers two amoCRM pipelines. Extra pipelines come as blocks with their own field mapping and qualification scenarios.
3
Assistant scenarios
The base scope includes three scenarios: lead qualification, follow-up, and manager handoff. Each scenario runs on a test pipeline.
−70%
Request handling
In the retail-support-bot case the request handling time dropped by 70%. The assistant removes context gathering and first replies.
What the delivery includes
Pipeline and field map
After the audit you get the pipeline schema, the list of fields for reading and writing, the dedup rule, and the handoff points to a manager.
Pilot assistant
The assistant works on your test pipeline: it qualifies leads, sends follow-ups, and updates cards. The pilot runs for two weeks with a daily review.
Metrics dashboard
The dashboard shows the share of qualified leads, the tasks created by the assistant, card edits, and the time to first reply. Metrics come from amoCRM.
How the system is built
Lead context
The assistant pulls the conversation history, deal stage, amount, and past tasks for the lead from amoCRM before the first question, so the customer gets straight to the point.
Qualification
The assistant qualifies the lead against your script: it records budget, timeline, role, and interest in the fields, then sends a follow-up, so the manager calls with full context.
Handoff with context
On escalation the manager gets the transcript, the reason for the handoff, the collected fields, and the next step, and the dialog continues from the same point.
Where the solution pushes back
- 01
Pipeline setup quality
Assistant accuracy rests on labeled stages and required fields. During the audit we fix the pipeline schema, and consistent cards give the model precise context.
- 02
amoCRM API limits
amoCRM sets quotas on requests per second. We queue the writes through Kafka, keep the peak within the quota, and update cards at an even pace.
- 03
Money decisions stay with a manager
A person confirms discounts, refunds, and write-offs. The assistant gathers context, prepares the calculation, and creates a task, while the final word stays with the manager.
Technologies
The technologies we use in our work and their role in a project.
amoCRM and the event flow
The assistant reads leads and deals from amoCRM through the API and webhooks, events move through Kafka, Redis holds the dialog state, scenarios run on Python, and a snapshot of the cards sits in PostgreSQL.
Cost calculator
This is an indicative range, not a quote. We scope the exact estimate after a brief: it depends on volume and the number of integrations.
Pipelines
Users
Scenarios
Add-ons
Support
Year one: updates and monitoring, a reply within 2 business days.
Service
AI assistant for amoCRM: leads, deals, and conversations
The estimate covers our team's work. Hardware, third-party service licences and travel are added on request.
Estimated cost
₽990,000
Timeline
5 wk
Frequently asked questions
Which channels connect?
Website chat, email, Telegram, and WhatsApp. Every channel arrives through its API and webhooks and lands on one deal.
How does the assistant handle duplicate leads?
Before it writes, it looks for matches by phone, email, and company name. We fix the dedup rule during the audit and log every merge.
How long does the rollout take?
The pilot takes two weeks on one pipeline. The launch with several scenarios and channels starts in week four.
What does a manager get on handoff?
The dialog transcript, the escalation reason, the collected fields, and the next step. The manager continues the conversation without repeat questions.
What teams add to this service
Related Services
Part of Solutions
Implementation Examples
−70%
Request handling time
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