Commercial Proposal Calculation

Automation closes the loop from a pricing request to a finished commercial proposal. The AI agent takes the deal parameters, applies pricing rules, and assembles the document from a template — without switching between spreadsheets, CRM, and email. The manager receives a draft proposal and focuses on review and communication with the client.

The specific process looks like this:

1. The manager records the client request in CRM or initiates the calculation via an internal form.
2. The agent reads the deal parameters: service composition, volume, term, client segment.
3. The system cross-checks the parameters against the current price list in the file storage.
4. Discount rules are applied: by volume, by segment, by contract duration, by payment type.
5. A structured proposal is generated with the final price and a line-item breakdown.
6. The document is assembled from a template in the file storage via merge fields.
7. The draft proposal is attached to the deal card in CRM, and the manager receives a notification.
8. Optionally, the agent prepares the text of a cover letter taking into account the deal context.

What automation does NOT do

• It does not make decisions on individual discounts — deviations from the price list are approved by the manager or the head of sales.
• It does not send the proposal to the client automatically: the final check of prices, breakdown, and details always rests with a human.
• It does not replace the negotiation process — the agent prepares a correct calculation, not a dialogue with the client.

Where the effect occurs

Automation eliminates the two main sources of errors from the sales team's pain point list: manual parameter entry and inconsistent application of discount rules. A manager assembling a proposal manually copies prices from an old proposal, recalculates against an outdated price list, or forgets to apply a volume discount. Automation removes these patterns through a single source of truth — the price list in the file storage with a defined update policy.

In companies with multi-parameter services — consulting, agencies, SaaS with pricing plans — manual calculation takes up a significant portion of a manager's working day. After implementation, calculation time is reduced to minutes, and pricing errors are eliminated through verifiable logic. The manager frees up time for negotiations, lead qualification, and objection handling — tasks that directly affect conversion to sale.

The automation is built on a low-code platform and assembles a chain between the CRM, file storage, and the AI agent. The central element is an orchestrator on a workflow engine or equivalent, which accepts a trigger from the CRM and guides the deal through the calculation stages.

Technical flow:

1. Trigger: a manager creates a deal in the CRM or changes its status to «Proposal Preparation».
2. A webhook passes deal data to the orchestrator: client, services, volume, timeline, segment.
3. The agent loads the current price list from file storage (Google Drive, Dropbox, SharePoint).
4. A discount matrix is applied: rules are read from the same file storage or from the CRM configuration.
5. The AI agent on an AI model processes the deal context and prepares a breakdown: justification of the final price, comments on the service composition, typical objections.
6. The proposal template (docx or Google Docs) is populated via merge fields: client details, composition, prices, timelines.
7. The completed file is saved to the deal folder in file storage.
8. The proposal link is attached to the deal card in the CRM, and the manager receives a notification.
9. Optionally, the agent prepares the text of a cover letter, which the manager reviews before sending.

Typical configuration options

• Simple option: fixed price, 3-5 discount rules, one proposal template. Implementation takes 2-4 weeks.
• Medium option: multiple customer segments, separate price lists by product, a configurator with 10-15 parameters. 6-10 weeks for implementation and debugging.
• Complex option: multi-tier pricing, ERP integration, multilingual templates, discount approval in Slack. 12-16 weeks for the project.

Solution components

Alternative approaches

A fully coded solution in Python with LangChain offers more flexibility, but requires a development team and several months for implementation. Ready-made CPQ systems (Configure-Price-Quote) address the task out of the box, but cost more in subscription and integrate poorly with local CRMs. Grow2.ai's low-code path is the middle ground: fast implementation, transparent logic that an in-house analyst can refine without involving developers.

Security and compliance

Deal data does not leave the company perimeter: price lists and templates remain in the corporate file storage, and the orchestrator runs in a private environment. The AI agent receives only the context required to generate the breakdown, without exporting the customer base. If needed, the AI processing component can be replaced with a local model or skipped entirely — and the system operates as a deterministic rule-based calculator.

To launch automation, you need a basic digital infrastructure and several artifacts from the sales team.

Data and systems

• A CRM with a Deal entity and an open API or webhook: HubSpot, Salesforce, amoCRM, Bitrix24.
• File storage with access controls: Google Drive, Dropbox Business, SharePoint.
• An up-to-date price list in a structured format — a table, not a PDF.
• A proposal template in an editable format (docx, Google Docs) with a clear merge-field system.
• A description of the discount matrix: which discounts apply, under what conditions, and who approves them.

Team readiness

• A head of sales ready to formalize the current calculation process.
• An automation owner within the company — the person who tests proposals on the first wave of deals.
• An IT specialist or integrator for access to the CRM and file storage during the setup stage.

Process readiness

• The price list does not change weekly — if prices fluctuate, an update policy is needed first.
• The proposal template has been approved by legal: automation replicates the document rather than rewriting it for each client.
• Managers fill in the deal in the CRM correctly — incorrect input data produces incorrect proposals as output.

Timeline

A project with 'week' complexity fits within 2–4 weeks given a ready base of price lists, templates, and defined rules. Week one — process audit and artifact preparation. Week two — orchestrator and integration setup. Week three — a pilot on 10–15 deals with logic adjustments. Week four — launch in production mode and handover to managers.