Integration of the analytics system with the Database in Tables

Budget: 18000 UAH Deadline: 7 days

I can approach this as a technical adjustment of the system to a working state, but the budget of 5000 UAH here will most likely only cover a short audit or one narrow issue. For the first stage, I would allocate 7 days and 18000 UAH - stabilization of synchronizations, checking Supabase, Make.com, Google Sheets, basic alerts, and a plan for improvements on AI evaluation of calls =)

> I would start with a data flow map - CRM, telephony, advertising, Supabase, tables
> Next, I would check places where there are duplicates, gaps, manual launches, and scenario failures
> Then I would tidy up the PostgreSQL schema - types, indexes, relationships, breakpoints
> Separately, I would extract AI agents for transcripts - testing on several real calls, comparing evaluations, working standard

Look, there’s a nuance here - if the owner needs to see expenses, income, ROAS, leads, creatives, approval rate, and manager evaluations every morning without manual actions, then this is no longer a table, but a small management system. It can be kept simple, but it needs to be stable and observable.

I would clarify 2 things
> whether there is access to Meta Ads API, CRM, telephony, Supabase, and Make.com
> whether there are already approved criteria for AI evaluation of managers, or if they need to be refined together using call examples

Similar logic cases from Ingello
> https://business.ingello.com/forma-bpm - process automation and state control in the business system
> https://business.ingello.com/forma-crm - CRM logic, roles, metrics, and operational analytics
> https://business.ingello.com/vorfahr - AI and automation, close to the task with agents and reports

Main page for the exchange - https://systems-fl.ingello.com/ua

!!I would not sell this as a cosmetic improvement of the table!! It’s better to do a short technical phase, eliminate chaos in synchronizations, and then calculate the full improvement of dashboards and agents more accurately. Expand

Budget: 5000 UAH Deadline: 5 days

Hello! I see the headache: the system is 90% assembled, and the final 10% of "micro-details" are consuming all your energy. This is exactly what I will close — so that the table updates itself, and you just open the finished picture in the morning.

What I will do first (this is the core of your pain):

1. Stabilization of synchronizations. The most common reason for failures is API limits, timeouts, and incorrect JSON in the responses from the dashboards. I will set up an Error Handler in Make.com with retry and deduplication to avoid duplicates and omissions. On top — alerts in Telegram: if the scenario fails, you immediately see WHAT exactly did not pull through.

2. Auto-dashboard for the owner. I will bring the Google Sheet to a state where it updates without any manual launch: metrics by dashboards (expenses/income/ROAS/leads), the state of creatives (burnout by frequency + drop in CTR), approve rate by managers.

3. AI evaluation of calls — this is my specialty. I will build agents that evaluate conversations based on clear criteria (quality, handling objections, adherence to the script, overall score). I will set it up: the agent takes the transcript from Supabase → analyzes → writes the result back to the table. Together we will run several real transcripts, compare approaches, and fix the best one as a standard.

I will audit the Supabase schema (types, indexes, relationships) + breakdown of expenses by niches/products and Meta Ads API as a separate stage, so as not to inflate the first one — first, we eliminate manual work.

To assess accurately: give access to Supabase and to the Make scenarios — I will see what is failing, and in the first step, I will show a working synchronization + alert on one dataset.

Cost: 5000 UAH (first stage). Deadline: 5 days. Expand

Budget: 5000 UAH Deadline: 6 days

Good day! I specialize in such connections — I have done synchronizations between Supabase and Google Sheets using Python with alerts in Telegram when a scenario fails or duplicates data. To assess the scope — do you have access to Supabase and the scripts that are currently pulling data from the CRM and dashboards? This will determine whether it's a quick stabilization or if part of it needs to be rewritten. I will also handle the dashboards and transcript analysis through an agent so that the table updates automatically without manual triggering. Approximately 5-6 days.

Budget: 5000 UAH Deadline: 1 day

Hello! I am ready to take on your project and will complete it urgently. I have extensive experience with similar tasks, so there will be no difficulties. If I have piqued your interest, feel free to write; I am happy to collaborate!

Budget: 5000 UAH Deadline: 2 days

In such integration, synchronization often fails: duplicate rows, misaligned columns, different date formats, and manual edits in Google Sheets.

I will set up the Supabase/PostgreSQL → Google Sheets connection so that the table updates predictably and can be read without cleanup after each import.

I will start by checking the structure of the tables and the required data slice, then I will create a script or integration with logs and a retry mechanism in case of failure.

If needed, I will immediately establish column mapping for your current table to avoid breaking the usual workflow.

I can start today; please send access or a test project — for the first stage, I will demonstrate working synchronization on one dataset.

Budget: 5000 UAH Deadline: 10 days

Hello!

I completely understand your fatigue from "catching micro-details." When an automation system is cobbled together using No-code tools like Make, it inevitably starts to fall apart in edge cases (duplicates, omissions, hangs). I specialize in Data Engineering, developing stable ETL pipelines, and optimizing databases (PostgreSQL / Supabase), so I will refine your prototype.

Here’s how we will address the technical issues of the system:

Stabilizing Supabase and anti-duplicate: I will tidy up the database itself. I will define clear unique constraints, check data types and indexes. If Make tries to throw in a duplicate, the database will simply reject it at the architecture level.

Logging and alerts: I will set up transparent monitoring. If any synchronization (CRM or telephony) fails, the system won’t just go silent; you will receive a clear notification (for example, in Telegram) about what exactly failed and at which stage.

AI analysis of transcripts: Since the transcripts are already in the database, I will set up a worker script. It will take the raw text, run it through prompt engineering according to your criteria (script, objections, evaluation), and automatically record the structured result back into Supabase/Sheets. Together, we will test the quality of the output on real calls.

Automated dashboards: I will optimize data transfer to Google Sheets so that formulas do not "hang" the sheet and the owner does not have to click manual updates every morning.

I write clean code that works autonomously. I am ready to take a look at your Supabase schema and Make scenarios today, find weak spots, and close this task once and for all. Looking forward to chatting! Expand

Budget: 5000 UAH Deadline: 7 days

Hello! I understand your pain - the "gluing" stage of the prototype is always the most exhausting, as it hides micro-failures that consume all your time. I specialize in stabilizing such systems (Make + Supabase + Sheets). My goal is to ensure that you don’t "control" the data, but open a dashboard and make management decisions. Here’s how I propose to change the approach to eliminate routine:

Stability instead of "crutches": Instead of simply "repairing" scenarios, I will implement an Error Handling system in Make.com. We will set up a separate monitoring scenario that will check the integrity of the data in Supabase and send you a specific message in Telegram, not just an error: "Data from CRM did not arrive, check the API key." This will relieve you of control.

Automation of dashboards: The problem of "manual updating" often lies in the fact that tables are overloaded with queries. I will optimize the structure in Supabase (PostgreSQL) so that Google Sheets receive already prepared, aggregated data via API, rather than "raw" junk.

AI agents for calls: I already have ready-made solutions for analyzing transcripts. We won’t just "evaluate"; we will set up a trigger: if AI detects a critical script violation - you will receive an alert in the same Telegram.

Database optimization (Supabase): I will tidy up the data types and indexes. This will speed up dashboard updates significantly and eliminate "freezing" during synchronization.

Why this is beneficial for you:
We will move from a "patching holes" mode to a "stability support" mode. You will receive a tool that requires attention only in case of real failures, not daily intervention.

What I propose as the first step:
Let’s start with an audit of one critical link (for example, the connection CRM -> Supabase). I will analyze the logic in Make and immediately point out where the database is "ailing".

I am ready to take on this "exhausting" part of the work so that you finally get a system that works for you, not the other way around. Which part of the system is currently breaking most often? Expand

Budget: 11000 UAH Deadline: 7 days

Good day. I am ready to take your project to work. I can analyze your automations and add new ones according to your specifications. Message me privately, we will discuss the details of your specifications and can start the implementation.

Budget: 5000 UAH Deadline: 7 days

Good day, Ruslan! I will stabilize the synchronization: I will go through all the Make scenarios, find where it hangs/duplicates/skips, set up the Error Handler + Telegram alerts to immediately see what hasn't been pulled in. I will set the dashboard to auto-refresh - metrics for the accounts (ROAS, expenses, leads, CTR), status of creatives by frequency and CTR, approval rate of managers - the owner opens the table in the morning and sees the current picture. For transcripts: the agent retrieves from Supabase → analyzes through Claude API (quality of conversation, handling objections, adherence to the script, overall rating) → writes the result back to the table. I will tidy up the Supabase schema: data types, indexes, relationships between tables where it can break or accumulate junk.

Budget: 5000 UAH Deadline: 1 day

Hello! I carefully read the technical specifications — five tasks, I understand each one.

By points:

Synchronization — I will check all Make.com scenarios, find where they fail, and set up alerts in Telegram for failures. Data should update without manual intervention.
Dashboard in Google Sheets — I will connect to Supabase via API or Make, data will be pulled automatically. Metrics on accounts, creatives, CTR, approve rate — all in one table that updates itself daily.
Additional metrics — I will connect to the Meta Ads API, breakdown of expenses by niches/products directly in Supabase. If there is no access to the API — a manual input form for 3-4 fields with automatic saving.
AI evaluation of calls — I will take the transcript from Supabase, run it through Claude/GPT with evaluation criteria (quality, objections, script, overall score), and record the result back in the table. We will initially test on real transcripts and calibrate.
Normalization of the database — audit of data types, indexes, relationships, correction where data is accumulating incorrectly.
I know the stack: Supabase, PostgreSQL, Make.com, Google Sheets API, Meta Ads API, Claude/GPT API.

Write to me — we will discuss the details. Expand

Budget: 27000 UAH Deadline: 12 days

We already have a nearly ready similar solution for analytics on Supabase, Google Sheets, advertising metrics, and AI evaluation of calls - it can be quickly adapted and launched, in touch ))

Regarding the budget - 5000 UAH will be enough for a short audit and a list of corrections, but stabilizing synchronizations, dashboards, alerts, Meta Ads API, AI analysis of transcripts, and database verification are more like a stage starting from 40000 UAH and 10-12 working days.

We can keep it simple - I would leave Google Sheets as a temporary screen for the owner, and make Supabase the single source of data. We remove manual launches, critical updates are included in planned processes, and we add an error log and notifications to see where the record did not pull through.

Regarding the dashboard, I see an important nuance - this is not just data pulling, but a daily management tool. Separately, I would check ROAS, leads, expenses, approve rate, creative burnout by frequency and CTR, and AI evaluation of managers based on transcripts.

Access to Supabase, Make.com, Google Sheets, CRM, telephony, and advertising accounts is needed. It is also worth providing 3-5 examples of real calls to compare the evaluations of different AI approaches and not to mix up a good idea =)

I would like to clarify 2 things.
- Is the Meta Ads API already available in your account, or do we need to create a backup option with a manual form?
- How many call transcripts need to be evaluated per day?

Similar cases from Ingello.
- https://business.ingello.com/platforma - corporate platform with business logic, roles, and operational analytics.
- https://business.ingello.com/forma-bpm - process automation and execution control without manual support.
- https://business.ingello.com/fractal - AI agents and automation of complex workflows.

The main profile on systems and automation - https://systems-fl.ingello.com/ua Expand

Budget: 25000 UAH Deadline: 12 days

Hello
unknown factors affecting the price
For an accurate assessment, I need to see:

number of Make scenarios;
CRM (which one);
telephony (Binotel, Ringostat, Zadarma, etc.);
number of tables in Supabase;
sample of the current dashboard;
we need to divide this into 5 tasks
1 per task
write to me and we will agree. Expand

Budget: 5000 UAH Deadline: 5 days

Hello! I am gathering exactly such data pipelines: CRM + telephony + advertising cabinets → Supabase → Google Sheets, so that everything updates automatically, without manual control.

What I will do:
— bring current processes to a stable auto-mode (remove manual steps);
— reliable connections via API/webhooks with error handling and retries, so that data does not "drop";
— clear summary tables that can be relied upon for decision-making.

I work with Supabase/SQL/API daily, and I built my own AI-CRM from scratch.

I am ready to look at the current system and tell you what specifically is "leaking". Approximately 5 days.
Matviy Expand

Budget: 5000 UAH Deadline: 5 days

Hello!

We can help with stabilizing your analytics system. We work with internal tools, automations, Google Sheets, databases, dashboard systems, and AI integrations.

From the description, I see that the main issue is not just with integration, but with the stability of the pipeline: synchronization, duplicates, data loss, alerts, and quality control. We can start with an audit of the current logic, identify critical points, and fix the initial problems in Supabase / Sheets / automations.

In the first phase, I propose to:

check the current structure of the database and synchronization;
find the causes of duplicates or data loss;
set up basic logging / notifications;
fix 1–2 critical scenarios.

I consider a budget of 5000 UAH for the first phase. After the audit, I will be able to accurately assess the full stabilization of the entire system. Expand

Budget: 5000 UAH Deadline: 14 days

I understood the task: to bring the analytical framework to a state where the owner opens the spreadsheet every morning and sees the current picture without manual updates. Everything revolves around Supabase, Make.com, Google Sheets, plus AI agents for evaluating call transcripts and recommendations for creatives.

The action plan looks like this:

First — go through all synchronizations (CRM, telephony, advertising accounts, Supabase, Sheets), find points where it fails, duplicates, or requires manual initiation. Set up alerts in Telegram or Slack for missed runs, structured as follows: a separate status log in Supabase plus a simple watcher that checks daily that all sources have pulled fresh data.

Second — dashboards in Sheets. If Make.com struggles with speed on large volumes, direct IMPORTRANGE plus cached views in Supabase usually pull the same picture faster and more reliably. I will consolidate ROAS, expenses, CTR, leads by accounts into one table with triggers for creative burnout. Approval rates by managers and AI evaluation from transcripts will be automatically updated from the respective Supabase tables.

Third — additional metrics from the Meta Ads API. You already have integration through Make, so I will only add the missing fields (by niches and products) through a separate job. If API access is not granted for some advertisers, a simple web form with 3-4 fields in Google Form with a direct webhook to Supabase, without intermediaries.

Fourth — transcripts and AI agents. I always do it this way: the pipeline reads the raw transcript from Supabase, sends it to LLM with a system prompt based on criteria (quality, objections, script, evaluation), receives structured JSON with evaluation plus quotes from the text, and writes it back as a separate line. Running on ten real transcripts and comparing models (Claude Sonnet against GPT-4, possibly Haiku as a quick option) gives us a working standard. In production, I have already created a similar pipeline for customer conversations through RAG plus an agent layer in a voice AI assistant.

Fifth — Supabase audit. I will go through the schema (types, indexes, foreign keys, places where data may duplicate), compile a short report with suggestions and corrections. If there are points where it’s easier to rewrite under SQL view instead of Make flow, I will say it directly.

Questions that are usually resolved immediately: what is the volume of data in Supabase (thousands of rows or millions, as this affects whether materialized views are needed), how many advertising accounts we are looking at, and which LLM provider is already being used, to avoid creating separate accounts and keys.

Based on experience with this stack: I have done integrations in production with Supabase plus LLM agents for voice AI service and RAG search, agent orchestration through MCP, audit cycles for data and security. I am ready to discuss the details in a call for 15-20 minutes. Expand

Budget: 10000 UAH Deadline: 7 days

Hello. I have extensive experience in process automation. I am ready to complete the task.

Budget: 5000 UAH Deadline: 1 day

Hello! 👋

I am a developer with experience in creating analytical systems.

My skills include:
✓ SQLAlchemy and working with databases (PostgreSQL, MySQL)
✓ Data processing and analysis
✓ API development
✓ Synchronization with Google Sheets and other services

In my portfolio:
• Web panel with monitoring and analytics
• Integration of various database systems

For your project, I will develop:
1. Reading and validating data from the database
2. Processing and analyzing information
3. Synchronization with tables (Google Sheets or other)
4. Dashboard for viewing results

I am ready to start working immediately. I can provide a detailed implementation plan.

Thank you! 💪 Expand

Budget: 8000 UAH Deadline: 10 days

Make scenarios are failing, data is duplicated, manual checks instead of work — a classic picture when automation grew gradually and no one laid the foundation.

Here’s what and how:

Synchronization. I will go through all active scenarios in Make, check the logs + Supabase logs, find where and why they are failing. Where there is an INSERT — I will switch to UPSERT, where there are duplicates — I will clean up and close with logic. I will set up an alert so you see the problem immediately, not the next day.

Dashboard. Expenses, income, ROAS, leads, CTR for each account — automatically, without your intervention. The owner opens Sheets in the morning and sees the current picture.

AI call evaluation. New transcript in Supabase → Claude API (objections, script, overall manager rating) → result in Sheets. I will do it through n8n — it’s better than Make here due to the native Supabase node. From the first commit to a working pipeline takes 2-3 days.

Meta Ads. A long-lived token and Marketing API access are needed. If access is available — I will connect through Make. If not — there is an application, review takes up to a week; in parallel, I will create a manual input form with 3-4 fields as a backup option.

Database. Audit of types, indexes, relationships — I will fix where the schema breaks or accumulates junk.

I propose two stages:

Synchronization + dashboard → 8,000 UAH, 5-7 days — results visible immediately.
AI call evaluation + Meta Ads + Database → 12,000 UAH, 7-10 days.
If we need to focus on the main thing now — we start with the first, then you will decide whether to continue.

Please clarify: how many scenarios in Make are currently active? And are the transcripts in Supabase already in text format or do we need to transcribe the audio? Expand

Budget: 8000 UAH Deadline: 3 days

Good day.
Our team has many years of experience in developing ERP, CRM, CMS, and specialized software for businesses. We create effective digital solutions that help automate processes, increase productivity, and scale companies.

We work with modern technologies — from bots and scripts to AI agents and analytical systems. We develop websites of varying complexity. In our portfolio, we have implemented ERP solutions for the hotel business, as well as for companies engaged in the import and sale of goods, and our own product XFitness — an ERP system specifically designed for fitness clubs.

We are ready to implement your project and offer the best solution tailored to your needs.
Our portfolio: Freelancehunt

We specialize in the following areas:
- Development of ERP Systems
- Development of CRM Systems
- Development of Websites of any complexity
- Development of CMS Systems
- Support for Websites
- Development of OpenCart
- Support for OpenCart
- Modification of OpenCart
- Enhancement of OpenCart
- Development of WordPress
- Support for WordPress
- Modification of WordPress
- Enhancement of WordPress
- Development of ECommerce
- Support for ECommerce
- Modification of ECommerce
- Enhancement of ECommerce
- Development of Web Applications
- Support for 1C Servers
- Support for Web Servers
- Development of mobile applications
- Data parsing
- Development of bots
- Development of AI agents

and on the following technologies:
- Python
- PHP
- Laravel
- Symfony
- Yii2
- JS
- NodeJS
- jQuery
- TypeScript
- MySQL
- HTML
- CSS
- Vue
- Nuxt.js
- React
- React Native
- C++ Expand

Budget: 5000 UAH Deadline: 1 day

Good day!

My topic is data stabilization, automation, and AI agents. Your stack is completely my working environment (Supabase/PostgreSQL + Make + Google Sheets + Meta API), so I can jump right in. I see that you have almost completed the system and are tired of the micro-details — I will help you get it to a state where it works on its own.

As I see it by the blocks:

Synchronization — I will go through all the scenarios in Make (CRM, telephony, advertising accounts, Supabase, Sheets), find those that crash, hang, duplicate, or skip records. I will fix them and set up alerts for failures — so you can see exactly where the problem is and what didn’t pull through, rather than searching manually.
Owner dashboards — I will turn it into a daily tool that updates itself: metrics for each account (expenses, income, ROAS, leads), the status of creatives (burnout by frequency and drop in CTR), approval rate by managers, recommendations, and AI assessment. Morning → open the table → see the current picture without manual pulling.
Additional metrics — breakdown of expenses by niches and products; if there is access to the Meta Ads API — I will pull directly, if not — a simple form with 3-4 fields that writes to Supabase.
Transcripts → AI agents — I will set up the process: the agent takes a transcript from Supabase, evaluates it based on criteria (quality, objections, script, overall score) and writes the result back. Together we will run real transcripts, compare different skills/approaches, and fix the best one as a standard. This is exactly what I have worked on a lot.
Supabase database — I will go through types, indexes, relationships, find places where data breaks or accumulates incorrectly, and suggest specific corrections — so that it is a proper tool, not a "tweaked prototype."
If I see a simpler solution than the current one — I will suggest it right away, that’s what you’re after.

It’s better to proceed in stages (first stabilization of synchronizations + alerts — because this is the foundation, then dashboards, metrics, AI transcripts, database). What is the most urgent for you to start with — are the synchronizations crashing right now or are the dashboards causing the most pain? Expand

Budget: 5000 UAH Deadline: 1 day

Good day! We have experience working with Supabase, PostgreSQL, n8n, Google Sheets, and AI agents. We can help bring the current analytics system to a stable working state without manual oversight. What we will do:
• audit all integrations (CRM, telephony, advertising accounts, Supabase, n8n, Google Sheets);
• find and fix scripts that fail, duplicate, or lose data;
• set up monitoring and alerts for failures;
• refine the owner's dashboards with automatic updates;
• integrate additional advertising metrics through Meta API or alternative sources;
• connect AI analysis of transcripts with results recorded in Supabase;
• audit the database structure (indexes, relationships, performance, data quality);
• provide recommendations for simplifying and scaling the architecture.
The main goal is for the data to update automatically, allowing the owner to see current metrics and agent reports every morning without manual checks and launches. For an accurate assessment, it is necessary to review the current n8n architecture, Supabase structure, and existing dashboards.

Budget: 5000 UAH Deadline: 7 days

Hello! I am ready to complete your task, I have experience working on similar projects.

Budget: 5000 UAH Deadline: 2 days

Good day!

In your description, I see a typical situation where the system is almost working, but a large number of small technical debts have accumulated, causing the owner to constantly check something manually. I am particularly interested in tasks like these — not creating another prototype, but bringing analytics to a stable working state.

I can help with:

• auditing all current integrations (CRM → Supabase → Make → Google Sheets, telephony, advertising accounts);
• finding the causes of duplicates, missed records, freezes, and manual launches;
• setting up monitoring and error notifications;
• optimizing the structure of Supabase/PostgreSQL (data types, indexes, relationships, performance);
• automating dashboard updates without manual intervention;
• integrating AI analysis of transcripts with recording results in the database and tables;
• expanding advertising analytics through API or simplified data entry forms.

I see the approach as follows:

1. Conduct a technical audit of all data flows.
2. Eliminate critical points of failure.
3. Set up control and logging.
4. Bring dashboards to a state of "opened in the morning and saw the whole picture."
5. If necessary, suggest simplifying the architecture if some tasks can be solved cheaper and more reliably.

To assess the scope of work, I would like to clarify:
— through which telephony service is the data coming?
— which CRM and advertising accounts are connected?
— how many scenarios are currently running in Make?
— are there already ready-made AI agents for analyzing transcripts, or do they also need to be configured?

It seems that the main work has already been done, so the most valuable thing now is to carefully eliminate bottlenecks and make the system stable and predictable. I would be happy to help bring it to its final working state. Expand

Budget: 8000 UAH Deadline: 8 days

Good day, Ruslan.

I propose to bring your analytics to a stable state in 5 stages:
1. Audit of current synchronizations (CRM, telephony, advertising) — I will find all points of failure and duplicates.
2. Replacing Make.com with n8n or Go scripts for reliable ETL — this is simpler and more controllable.
3. Adding AI agents for analyzing transcripts and metrics (call quality, script, approve rate).
4. Finalizing the dashboard in Google Sheets with auto-refresh.
5. Optimizing the Supabase schema: indexes, data types, relationships.

Result: a daily up-to-date picture without manual actions.

A bit of detail:

Replacing Make.com with n8n or scripts will not complicate system maintenance, even if you want to change something yourself, as n8n allows for creating more robust scenarios with better error handling than Make.
I will set up the system so that the logic is transparent, and I will also provide a brief instruction so you can manage the processes without developer assistance.

To ensure that the data in Google Sheets updates automatically and without errors, as this is currently the main issue, I will implement an automatic monitoring and alerting system: if any synchronization stage fails, you will receive an instant notification.
Instead of simple "data dumping," I will set up integrity checks at the Supabase level, which will eliminate duplicates and gaps.

To ensure the accuracy of AI assessments of managers based on transcripts and to avoid it being just a "random" result, I will apply the Few-Shot Prompting method, providing the AI agent with several benchmark examples of conversations with your ratings.
We will test different models on real data together, compare results, and fix the most accurate prompt as the standard for the entire database.

PM: Source code and documentation included. Expand

Budget: 5000 UAH Deadline: 5 days

Hello! I understand your fatigue from constant manual adjustments — such connections often fail due to weak database architecture or lack of proper alerts.

I can stabilize your system.

Since you are open to new solutions, I strongly recommend migrating automation from Make to n8n. For large data sets and working with AI, it is significantly more stable, does not lose records, and allows for clear error tracking. I will also completely tidy up the Supabase structure (indexes, types, relationships).

Let me know if you plan to connect the basic OpenAI API for AI call evaluation, or if you already have your configured agents.

Budget: 5000 UAH Deadline: 3 days

Hello.

I see the need for a systematic approach to stabilizing your analytical infrastructure, which includes establishing end-to-end automation and optimizing current processes. My strategy involves a thorough review and refinement of existing pipelines in Make.com to ensure their idempotency, fault tolerance, and minimize manual intervention, with a focus on correct data architecture in Supabase and seamless synchronization with Google Sheets. To automate call evaluations, I will integrate agents using pre-developed modules for natural language processing and recording results in the database, which will allow for business recommendations without human involvement. I have significant experience in deploying similar solutions for collecting and analyzing business metrics, using optimized scripts and templates for the rapid implementation of a reliable monitoring and alerting system. As a result, you will receive a fully autonomous analytics system with intelligent monitoring, allowing you to focus on the business. I suggest discussing all implementation details, final budget, and timelines in personal messages.

Budget: 5000 UAH Deadline: 5 days

Hello!

I see the task involves stabilizing Make.com integrations, building dashboards based on Google Sheets, and setting up an AI pipeline for analyzing call transcripts with data uploads to Supabase.

I have relevant experience for your tasks:
— Data pipelines: I have developed and launched robust data processing pipelines on Node.js and Python for synchronization with external APIs.
— Database architecture: I have designed audited balance ledgers with transaction logic (similar to Supabase) and set up webhooks without duplication.
— Applied LLM solutions: I have developed and implemented multi-agent systems for analyzing text dialogues and transcripts.

Approach and estimate (approximately 70–155 hours): To ensure a stable start, I suggest beginning with a small paid phase of Audit and Discovery (8–15 hours). This will allow us to analyze existing Make scenarios, the structure of Supabase, and assess the state of integrations before fixing timelines.

Project stages:

— Audit and Discovery: 8–15 hours.
— Stabilization of Make scenarios: 12–28 hours.
— Google Sheets dashboard: 12–25 hours.
— Integration of Meta Ads API or manual entry: 6–22 hours.
— AI pipeline for analyzing transcripts to Supabase: 14–28 hours.
— Normalization of Supabase DB (schemas, relationships, indexes): 10–22 hours.
— E2E testing and project handover: 8–14 hours.

Key risks to consider:

— Make.com is sensitive to failures; it’s better to move some calculations to Supabase (pg_cron + Edge Functions) for stability.
— Google Sheets is not a database; Apps Script often fails under load. Sheets should only be a presentation layer.
— The complexity of the Meta Ads API heavily depends on the available access levels and tokens.
— The quality of AI analysis of transcripts requires joint calibration of prompts.

A few clarifying questions:

1) Is there already approved access to the Meta Ads API, or does it need to be obtained from scratch?
2) Are you ready to migrate critical logic from Make.com to native Supabase solutions?

I propose collaboration through a "Safe Deal" on Freelancehunt, dividing the work into clear stages.

I would be happy to discuss the project in more detail in private messages. Expand

Budget: 5000 UAH Deadline: 1 day

Hello. I am ready to complete the project turn-key, guaranteeing quality and promptness.

Feel free to message me, I would be happy to collaborate!

Budget: 14000 UAH Deadline: 8 days

Hello! I have experience with Make.com + Supabase + Google Sheets and building AI agents — exactly what you need for your project: I will stabilize the synchronizations, bring the dashboards to automatic updates, and connect transcripts to the agents in 8 days (14,000 UAH). I hope for cooperation!

Budget: 5000 UAH Deadline: 3 days

Good day!

I am ready to bring your analytics system to a stable, fully automated state. I have experience with Supabase, Google Sheets, Make.com, and API integration for advertising accounts. I will set up synchronizations, automatic dashboards, and AI call evaluations, bringing the database in order.

Message me privately, and we will clarify the details.

Budget: 5000 UAH Deadline: 2 days

Hello! I completely understand your pain. When the automation system is 90% built, those final 10% "micro-details" that fall off take the most effort.

Your stack (Supabase + Make.com + AI + Google Sheets) is very familiar to me. I specialize in creating AI agents, analytical bots, and optimizing databases. I am ready to take this routine off your hands, close all the "tails," and bring the system to full autonomy.

Here’s how I propose to solve your tasks:
Stabilizing synchronization (Make + Supabase):

I will find out why the scenarios are failing (usually it’s API limits, timeouts, or incorrect JSON response handling). I will set up Error Handler blocks in Make.com and connect alerts (for example, to a Telegram bot) so you can immediately see if any webhook or order did not go through.

I will tidy up the Supabase database: I will set up the correct indexes (for fast Google Sheets queries), and check Foreign Keys (relationships) to ensure data is not duplicated.

AI agents for calls and creatives:

Transcripts: Since the data is already in the database, I will set up a pipeline where the LLM (via OpenAI/Anthropic API or agent platforms) will evaluate the managers' work (script, objections) based on your prompt and automatically record scores/tags back into Supabase. Together we will test and calibrate the prompts.

Creatives: I will teach the agent to analyze CTR and frequency from Meta Ads and output ready recommendations in a table: "Turn off creative X (CTR dropped by 30%)".

Automated Dashboards (Google Sheets):

So that the owner does not have to update anything manually, we will optimize the data import from Supabase. Instead of heavy formulas inside the sheet that slow it down, the data will flow in already aggregated and ready for visualization. Expand

Budget: 5000 UAH Deadline: 5 days

Good day! We have experience in setting up data flow automation between Supabase and Google Sheets. We implement this through script optimization and trigger configuration, which will completely eliminate manual management and ensure synchronization stability. We are ready to take on the stabilization of your analytics system in the near future.