You will get Ask your CRM data questions in plain English with an AI assistant
Project details
"How many qualified leads did we get last week?" is a simple question that somehow always takes twenty minutes to answer — someone has to open Airtable, find the right filter, and count rows by hand. I asked some version of that question in pipeline reviews for seven years and watched the room wait on someone else's spreadsheet every time.
I'll build an assistant that skips the wait: ask it a plain-English question about your pipeline, and it translates that into a safe, read-only query against your real CRM data, then answers in seconds — no filter-building, no "let me check and get back to you."
This isn't a general chatbot bolted onto your CRM. It's scoped to the specific, high-value questions a sales team actually asks every week, and it's built to say "I'm not confident enough to answer that" rather than guess at a revenue number.
You'll get a working assistant wired into your CRM, documentation on exactly what it can and can't answer, and one round of tuning based on the real questions your team throws at it.
Tools I build in: Activepieces, OpenAI, Airtable, Slack.
I'll build an assistant that skips the wait: ask it a plain-English question about your pipeline, and it translates that into a safe, read-only query against your real CRM data, then answers in seconds — no filter-building, no "let me check and get back to you."
This isn't a general chatbot bolted onto your CRM. It's scoped to the specific, high-value questions a sales team actually asks every week, and it's built to say "I'm not confident enough to answer that" rather than guess at a revenue number.
You'll get a working assistant wired into your CRM, documentation on exactly what it can and can't answer, and one round of tuning based on the real questions your team throws at it.
Tools I build in: Activepieces, OpenAI, Airtable, Slack.
AI Algorithms
Large Language ModelAI Applications
Conversational AIAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$90
|
Standard
$200
|
Advanced
$340
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 8 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | |||
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | ||
Setup File | - | - | - |
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$15 - $25
Additional Revision
+$7Frequently asked questions
About Siddhesh
GTM Engineer | RevOps Automation, n8n, Make, GoHighLevel
Nashik, India - 8:28 pm local time
I design and build lead-to-cash automation — CRM architecture, lead routing, enrichment, AI scoring, and WhatsApp/form-to-CRM pipelines — for teams that are losing leads to slow, manual, or broken handoffs.
Flagship project: RevenuePilot OS, a 10-workflow B2B lead-to-cash system I built solo — capture, dedup, enrichment, AI lead scoring, territory routing, Slack alerts, weekly AI reporting, and a natural-language revenue assistant. Built on Activepieces, Airtable, Slack, Gmail, and OpenAI.
I'm new to this platform, but not to the problem. I've spent 7 years on the receiving end of exactly what I now build — which is why I don't just wire up integrations, I build for how sales reps and managers actually use them day to day.
Available now. Let's talk about what's leaking in your funnel.
Steps for completing your project
After purchasing the project, send requirements so Siddhesh can start the project.
Delivery time starts when Siddhesh receives requirements from you.
Siddhesh works on your project following the steps below.
Revisions may occur after the delivery date.
Collect the questions your team actually asks
We gather the real questions your team wants answered about the pipeline — not hypothetical ones, the ones people actually ask in meetings.
Build the question-to-query layer
I set up the system that turns a plain-English question into a safe, validated query against your CRM data.