Budget: 3000 UAH Deadline: 3 days
Hello.
OpenAI API - experience with GPT-4, function calling, token management.
Telegram bots - aiogram, python-telegram-bot, multi-user solutions with history.
Prompt 12k - using GPT-4-turbo (128k context), system prompt fixed, dialogue through rolling window to stay within the limit.
Budget: 3000 UAH Deadline: 5 days
"Here I just formed the response through a similar bot of mine)) - besides this text"
1. I have experience integrating the OpenAI API in several projects, including the implementation of complex management logic and processing large system prompts with context consideration.
2. I have developed Telegram bots using the Bot API – from simple chatbots to complex CRM integrations and automation. For example, I implemented bots for customer support and data parsing from chat.
3. I handle long prompts by storing and dynamically forming the context of messages. To optimize, I use a combination of the system prompt with the user request, as well as minimal but sufficient context from the dialogue history. If necessary, I break the prompt into logical parts and embed them as several parameters in the request to OpenAI.
4. The preliminary deadline for completion is 7-10 days, depending on the clarification of details regarding logic and the need for stability testing.
I base my work on experience in PHP, Laravel, and Docker for stable and scalable bot deployment. I am ready to offer additional ideas for improving the interaction between the bot and the user and maintaining context in the future.
Budget: 3000 UAH Deadline: 7 days
Hello, I worked on a project with "tag:7748" - developing an AI chatbot for automating customer support with OpenAI API integration and complex request processing logic, handling 500+ dialogues/day.
How do you plan to handle the dialogue context when reaching the token limit of the OpenAI API with such a large system prompt of 12k characters?
I suggest we get in touch, I will consult you for free on the technical side and we will create a development plan + I will tell you about my team!
Budget: 3000 UAH Deadline: 4 days
Hello!
I can implement it. I will set up correct dialogue processing, context preservation, and predictable behavior. I have experience working with OpenAI, Telegram bots, and prompt engineering.
How I will implement it: I will move it to a separate configuration, optimize the structure (breaking it into blocks/roles), control the length of the context and dialogue history to avoid exceeding limits and losing logic. I will also anticipate error handling and stable interaction with the API.
Deadline: approximately 2-4 days.
Please let me know if it is necessary to limit the number of requests/users or to create a basic admin panel for usage control?
Budget: 3000 UAH Deadline: 4 days
Good day!
1. OpenAI API - I work regularly: chat completions, role management, generation parameters. I understand the difference between "connecting ChatGPT" and building a managed agent.
2. Telegram bots - I developed using aiogram 3, with multi-step dialogues, state storage, and integration of external APIs.
3. Working with long prompts
I store the system prompt in a separate file outside the code - it is loaded at startup and passed to the system field with each request, regardless of the dialogue history. The history is maintained separately in SQLite with a sliding window - the agent does not lose instructions even in long chats.
The architecture is modular: memory, agent logic, handlers - separate modules. In the future, it is easy to connect new tools or change components without rewriting the entire bot.
4. Deadline - 3-4 days after receiving the prompt and access.
Budget: 3000 UAH Deadline: 3 days
Andrey, I have reviewed the description — the task is clear and technically precise.
My stack: aiogram 3.x (Python) + OpenAI API — daily toolkit. I will implement the following: I will set up a bot on webhook (aiogram 3.x + FastAPI), connect OpenAI through the official SDK, configure the transmission of a 12k-character system prompt in the `system` role of each request without truncation. The conversational history will be accumulated in the `messages` array with a context depth limit — so that during long sessions we do not exceed the model's token limit. I will save the context through Redis or in-memory with TTL — we will clarify at the start. Regarding stability: API error handling (rate limit, timeout, retry with backoff), logging, deployment on Railway with auto-restart.
I will separately go through the agent's logic: I will check that the constraints and behavior from the prompt work predictably, without "breaks" in instructions.
One question: is the system prompt already finalized, or will it be adjusted during the process? This affects the number of testing iterations.
Budget: 3000 UAH Deadline: 3 days
Andrey, good afternoon. There is a case in the portfolio - a recruiting bot for Telegram with AI integration and questionnaire processing. I am writing in Python using the aiogram 3 library. I fix the system prompt at 12k characters in the system message with each request, and I store the context through a sliding window - the agent does not fall out of character. Deadline: 3 days. Budget: 3000. Write to me.
Budget: 3000 UAH Deadline: 2 days
I have experience in developing AI models and improving them through prompts, and I have also worked with the OpenAI and Gemini APIs. I have been working with Telegram for a long time as well. I am ready to complete the task quickly and efficiently; after discussing the details, I will suggest something that might interest you regarding how to improve all of this! Write to me.
Budget: 3000 UAH Deadline: 3 days
Greetings. I understood the task: a Telegram bot is needed that not only proxies requests but also strictly maintains a role based on a long 12k prompt, without deviating from the given context and logic.
I will respond point by point:
1. Experience with OpenAI API: I work closely with the API, including fine-tuning parameters (temperature, top_p) and the architecture of sending requests to keep the agent within system constraints.
2. Experience with bots: I have developed complex logic for Telegram bots in Python. For example, I created a bot for automating arbitration with optimized signal processing and a response time of less than 1 second. The bot operates seamlessly thanks to stable performance on a VPS. I have also implemented complex real-time alert systems in Telegram for risk managers.
3. Working with long prompts: 12,000 characters is about 3,000-4,000 tokens. The system prompt will be sent with the role of system with each API call to ensure the AI does not deviate from instructions. Basic context preservation will be implemented through a sliding memory window (storing the last N question-answer pairs). This will prevent context window overflow (Context Window Limit) and save you money on tokens while maintaining the thread of dialogue.
4. Deadlines: 2-3 days to implement a stable version with context caching. Which specific OpenAI model do you plan to use for testing (gpt-4o-mini, gpt-4o)? I suggest discussing the details in private messages.
Budget: 3000 UAH Deadline: 3 days
Good day!
I have reviewed your project — the task is clear, and I resonate with the approach of building a controlled AI agent rather than just a "wrapper" over ChatGPT.
1. Experience with OpenAI API:
Yes, I have experience integrating the OpenAI API, including working with system prompts, processing dialogue context, and controlling model behavior.
2. Experience with Telegram bots:
I have developed Telegram bots of varying complexity:
- bots with subscriptions and payments
- automation of business processes
- bots with role and state logic
- integrations with APIs and handling a large flow of users
3. Working with long system prompts (~12k):
I implement this through:
- clear separation of system/user/assistant messages
- optimization of prompt structure (if necessary — decomposition into blocks)
- control of context length (token management)
- maintaining a short dialogue history (memory) for stability
- additional checks to ensure the agent does not "deviate" from logic
If needed, I can suggest improvements in prompt engineering for more predictable behavior.
4. Timelines:
⏱ 3–5 days for MVP (a working bot with stable logic)
I will also ensure:
- stable operation without crashes
- clean and scalable code
- the ability to easily expand the project in subsequent stages
I approach such tasks not just as a performer, but as a developer who thinks about architecture and the future development of the product.
I am ready to discuss the details and start working.
Budget: 3000 UAH Deadline: 1 day
Good day!
I have 3+ years of experience in developing Telegram bots, AI automations, and integrations with the OpenAI API, including projects with non-standard logic, system prompts, and controlled agent behavior.
I can implement a Telegram bot with OpenAI integration, correctly embed a large system prompt, set up message reception and sending, basic dialogue context preservation, and stable operation without crashes and failures.
I suggest discussing the details, as well as the cost and timelines in private messages.
Budget: 3000 UAH Deadline: 1 day
Hello.
I am developing bots for Telegram using NodeJS. I am ready to take on the project. Write to me, and we will discuss.
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Budget: 3000 UAH Deadline: 7 days
Hello!
1. Yes, I have worked with the OpenAI API — integrations with agents, call analysis, data categorization through GPT.
2. I have created Telegram bots — I will show examples in private upon request.
3. I implement a long system prompt through the system role in each request, the dialogue context — through a sliding window to avoid exceeding the token limit. The prompt remains unchanged regardless of the dialogue volume.
4. Deadlines: 3-7 days after receiving the prompt.
Additionally, I suggest adding error logging and fallback responses — this is the stability you are requesting. Free of charge.
I am waiting in private.
Budget: 4000 UAH Deadline: 2 days
Hello. I can create this AI agent. I have some developments. If you are interested - write to me, we will discuss.
Budget: 3000 UAH Deadline: 3 days
has experience working with everything listed above.
long prompt is not a problem.
2-3 days
budget for MVP
Yehor Petrenko
Winning proposal- Projects 7
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Budget: 3000 UAH Deadline: 3 days
Good evening. Let's go point by point:
1. Yes, I have extensive experience with the integration of various AIs, including Open AI.
2. I have created different bots and various projects. Nothing demonstrates its ability to "think" except for the development of non-standard projects. I have made copies of bots, neural network bots, bots that consist of a collection of neural networks with specific settings.
3. Most likely, it is best to create such prompts through a "rule" in a specific neural network. When connecting via an API key (and not only), you can set a rule that the neural network will follow.
4. UP TO 3 days. However, usually, clients who respond quickly receive the work on the day of the order.
Budget: 3000 UAH Deadline: 3 days
Hello! I can implement a Telegram bot with OpenAI API integration and stable operation of the AI agent according to your system prompt. I have experience in creating Telegram bots using Python/aiogram, connecting APIs, processing messages, maintaining context, and managing dialogue logic. I have also worked with bots where it was important not just to respond, but to adhere to a given scenario and constraints. I will implement a long system prompt separately as the main instruction for the agent, keeping it stable in requests to OpenAI, and I will manage the dialogue context through a minimal message history so that the bot does not "get confused." I am ready to carefully analyze your logic and propose solutions so that the bot operates not as a regular ChatGPT, but specifically as a controlled AI agent.
Budget: 3000 UAH Deadline: 3 days
Hello. Interesting project. At least the prompt for 12k caught my interest. I will write in PHP, and a Telegram bot and AI integration. Feel free to contact me.
Budget: 3000 UAH Deadline: 5 days
Yes, I have experience working with OpenAI API and Telegram bots.
In my portfolio, there is a project - a bot for a salon, which operates on a similar principle (dialogue processing, communication logic, response automation), so I understand how to properly build the architecture of such a solution.
Regarding your project:
How I will implement work with a long system prompt:
I will extract the system prompt into a separate structure (to manage and update it conveniently)
I will use it as the base context for each dialogue
I will add length control for the context (to avoid overflow)
If necessary, I will break the logic into parts for more stable operation
Dialogue context:
I will implement basic storage (for example, through SQLite or JSON)
with a history limit for stability
Technologically:
Telegram Bot API + OpenAI API
processing incoming/outgoing messages
error and crash protection
Budget: 3000 UAH Deadline: 2 days
Let's go, I'll do it by tomorrow evening, but this is exactly the MVP to implement the idea, not an instantly scalable product, etc. Keep this in mind, I'll make it for you in Python with an OpenAPI schema that will be built upon push, hosting on Railway for $10 a month. If you need it, write to me now because I don't have much free time.
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Budget: 3000 UAH Deadline: 3 days
Hello! I am interested in your project. I have extensive experience in:
📊 Data processing: working with databases, structuring and analyzing information, automating the processing of large volumes of data, import/export and validation;
🤖 Automation and emulation of user actions, development of bots of varying complexity;
⚡️ Asynchronous and multithreaded parsing: collecting and processing data with performance optimization;
🔍 OCR and text search: recognition and structuring of information;
🖼 Media processing: working with images and multimedia;
🖥 Software development, desktop applications, system services and utilities;
📱 Mobile development: native and cross-platform applications;
🌐 Working with APIs and third-party services: integration, automation, and data exchange;
🗣 Translation and text processing: automation of translation, working with language models and text analytics;
🤖 AI/LLM solutions: integration and use of artificial intelligence, working with language models and automating intelligent processes.
I will complete the work quickly and efficiently. Contact me to discuss the details and deadlines of the project!
Proposals concealed
Proposals are currently absent
Budget: 27000 UAH Deadline: 14 days
Hello! I am the project manager of Business Atlas.
We specialize in creating autonomous digital ecosystems where AI agents take on complex communication logic. We have over 50 successfully implemented projects, and working with extensive system prompts is our specialty.
Here are our responses to your points:
• Experience with OpenAI API: Yes, we have significant experience in creating AI agents that independently conduct dialogues and perform the role of narrow specialists (from HR agents to accountants).
• Examples of Telegram bots: We have various solutions:
• AI SMM agent: independently collects news, generates text, and publishes posts.
• HR recruiting agent: intelligent scoring of resumes and automated job postings.
• AI agent for onboarding: conducting interviews and training new employees according to corporate regulations.
Working with long prompts (~12k characters): We understand that such a volume of instructions requires high precision in architecture. We implement this through:
Structuring the system role: Using a clear hierarchy of instructions (for example, through Markdown or XML tags within the prompt) so that the model does not "get lost" in the volume.
Prompt Engineering: we will focus on quick return on investment and stability of systems, so we will test the agent on "critical points" and adherence to prompt constraints.
Context management: We will set up basic context retention (Memory) so that the bot remembers previous messages without overloading the token window and maintaining logic.
• Deadlines: To implement a quality and stable MVP (Phase 1), we will need 7–14 days, including the testing and debugging stage of the bot's logic.
Cost of implementation for the stage: $1,500
We design the architecture so that in the following stages you can easily scale the bot to a full-fledged business assistant.
Write to me privately — we will discuss the details and can start.
Budget: 5000 UAH Deadline: 30 days
I can show as a reference my trading bot: it monitors the markets but has a full communication function. From my own experience, I can say: a system prompt of 12k characters is just the foundation; the main complexity and volume of work will be in debugging and "taming" the AI logic so that the agent does not hallucinate and clearly maintains boundaries during long dialogues.
For stable operation with such a volume of instructions, I will implement a dynamic context management system (token management) so that the bot does not "forget" its role when the message history starts to push out the system prompt. The budget and deadlines are in personal correspondence.
Which specific OpenAI model do you plan to use (GPT-4o or Turbo), considering the need for a balance between the accuracy of instruction execution and the limits of the context window?
Budget: 5000 UAH Deadline: 1 day
Good day. I am ready to complete this project and have extensive experience in developing various applications.
Budget: 13000 UAH Deadline: 5 days
Hello! I have extensive experience working with the OpenAI API and developing Telegram bots, including AI assistants with non-standard logic, dialogue memory, and complex system instructions. I implement a long system prompt through structured context management, token optimization, and reliable history storage, so that the agent operates stably and predictably. I can complete the first stage in 5-6 days, with the prospect of further project development.
Budget: 5000 UAH Deadline: 7 days
Good day, Andrey.
I have experience working with the OpenAI API and implementing long system instructions, where it is necessary not just to connect GPT via the API, but to achieve stable and predictable behavior.
As an example, the project "Shopify, Make, OpenAI — AI assistant for e-commerce" is in my portfolio. I have also worked with Telegram bots, so implementation for Telegram is not a problem.
Regarding working with long prompts: I first break it down into functional blocks (behavior, limitations, logic), then run it through interaction scenarios and iteratively refine it to achieve a stable result.
As for timelines, it is difficult to provide an exact figure at the start, as much depends on the number of revisions and the required quality of responses.
I am ready to discuss the details.
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Budget: 10000 UAH Deadline: 5 days
Hello!
Regarding your points:
1. Experience with OpenAI API
I work regularly — chat completions, function calling, structured outputs, streaming. I also use Anthropic (Claude) and Gemini, choosing the model based on the task. I know the current limits, retries, and handling of 429/5xx.
2. Telegram bots
I have created bots using the Bot API: text + voice (Whisper for transcription), inline menus, commands, callback buttons, integration with external APIs and CRM. Relevant experience includes a bot for receiving applications with parsing unstructured text through LLM into a structured format.
3. Working with long prompts (~12k characters)
12k characters is about 3-4k tokens, which easily fits in the system parameter. The important aspects are not the volumes themselves, but how the prompt is structured and maintained:
— The prompt is stored separately from the code (in a version-controlled file or database), so you can modify the agent's behavior without releases
— It is passed through `system`, not as the first user message — this is critical for the stability of following instructions
— I enable prompt caching on the OpenAI side — saves up to 50% of tokens on each response when reusing the prompt
— If there are strict limitations in the logic (prohibited topics, response formats) — I add post-hoc validation of the response, in case the model deviates from the instructions
— Dialogue context: the last N messages in the database (SQLite/Postgres), when exceeding the limit — rolling window or summarization of old messages
— I log dialogues so you can see where the agent fails and adjust the prompt accordingly
4. Deadlines
MVP according to the description — 5-7 working days:
— Day 1-2: bot framework, connecting OpenAI, basic dialogue
— Day 3-4: integration of the system prompt, context, testing edge cases
— Day 5-7: stability (retries, API error handling, logging), deployment on VPS, handover
Stack — Python (aiogram + openai SDK), self-hosted on VPS. I am ready to have a call or continue in writing.
Budget: 5000 UAH Deadline: 5 days
I will develop an AI agent for you with integration into Telegram. I have already worked on developing a bot for conducting dialogues and making sales of travel trips, I have experience. A long prompt can always be simplified using the same ChatGPT, keeping the key logical elements, which will make it work even better. Also, if there are too many instructions, key ones can be highlighted as a system prompt. The rest can be moved to a Vector Store. The context of the dialogue is maintained by passing the last 10-15 messages in the request, earlier messages are passed as a summary, which we generate separately every 15 messages. I would be happy to work on your agent.
Budget: 3000 UAH Deadline: 4 days
I have direct experience with OpenAI API and Telegram bots. Technical stack: Node.js/TypeScript, telegraf library for the bot, openai for working with the API. I will implement a long prompt (~12k characters) as a system message in requests. I will implement context management: dialogue history with token trimming to comply with model limits. Stability: API error handling, retry logic, logging. Portfolio: KasAgent (desktop AI agent with model routing) and Telegram store with an admin panel. Ready to start immediately.
Budget: 4000 UAH Deadline: 7 days
Good day! We have reviewed your project and are ready to effectively implement the first stage of the AI agent in Telegram with further scaling. We have practical experience in integrating OpenAI API, developing Telegram bots, and building AI logic for non-standard tasks.
What we can offer:
• Development of a Telegram bot in Python (aiogram / FastAPI)
• Full integration of OpenAI API
• Correct implementation of a large system prompt (~12k characters) considering stable operational logic
• Setting up dialogue context and message memory
• Error handling, logging, and protection against failures
• Flexible architecture for the next stages of the project
Answers to your questions:
1. We have experience working with OpenAI API — chatbots, AI assistants, process automation.
2. We have created Telegram bots of various complexity: client services, AI bots, CRM integrations, internal assistants.
3. The long prompt is implemented through a structured system instruction, dividing logic into blocks, token control, preserving agent behavior, and optimizing context.
4. The timeline for the implementation of the first stage: 3–7 days depending on the details of the technical specifications.
We approach tasks not as executors, but as a technical partner — we can offer optimal solutions for architecture and product development.
Our website: https://benefit-it.net/
Sincerely, Benefit Studio
Budget: 5000 UAH Deadline: 3 days
Hello. I have extensive experience in developing Telegram bots. I am ready for collaboration.
Budget: 3000 UAH Deadline: 3 days
Good day!
I am ready to implement a Telegram bot with OpenAI as a managed AI agent. I have experience with the OpenAI API and developing complex bots. I integrate a large system prompt, ensuring stability and logic. I maintain the context of the dialogue.
Message me privately, and we will clarify the details.
Budget: 3000 UAH Deadline: 10 days
Hello! I am Vladimir, the founder of the engineering agency Vaysed. Your project is our direct profile. We do not write primitive scripts; we build fault-tolerant AI architectures. I will respond to your points in order.
Firstly, we have extensive experience working with the OpenAI API. We integrate LLM into business processes where strict adherence to constraints and formats is required (for example, data parsing, working with checklists), completely eliminating model hallucinations.
Secondly, complex Telegram ecosystems are the main specialization of our agency. We create bots with state machine architecture that operate without failures. You can assess our engineering approach and examples of corporate bots on our website: https://vaysed.me/
Thirdly, how we implement work with a prompt of 12,000 characters. This is about 3-4 thousand tokens. If you simply chaotically stitch together the chat history and this prompt, you will quickly exhaust your API budget or break the logic of responses. The system prompt will be firmly fixed on our backend (Node.js or Python) under the role of System. To maintain context, we will implement a Sliding Window algorithm based on a lightweight database. The bot will keep only the most recent relevant messages in active memory, carefully cutting off old ones. This ensures that the AI will always "see" your strict instructions as a priority and will not lose focus.
Fourthly, the deadlines for completing this first stage (MVP with memory, integration of GPT-4o, and implementation of the prompt) will take 4-5 days of development.
I am ready to dive into the logic of your prompt, suggest optimal temperature settings for agent stability, and start working. Message me privately!
Budget: 25000 UAH Deadline: 15 days
Greetings.
I will answer right away that you will create the bot and the API as well. If I do it, then I will have full control. I will create a detailed instruction for you.
Next, we need to understand the scope of work for the bot; we need to select a server for it so that it can handle your requests.
OpenAI API is paid, even for tests you need to pay.
Setting up and adjusting this is not a problem.
Implementing memory is also not a problem, but here we again face the issue of what tasks need to be matched with the server.
We need to understand the full scope of work because later we will need to redo the entire architecture of the project.
Budget: 5000 UAH Deadline: 4 days
Hello. I have developed over 100+ bots, including Telegram. I connect AI agents not only from OpenAI, including setup with system_message. We also pay attention to the length of the context if needed. I use Go/Rust for development - as a choice.
We will implement this on the first day of development:
* Create a Telegram bot (Bot API)
* Connect OpenAI API
* Implement message reception/sending
* Integrate system prompt (~12k characters)
I think it will take about 2 - 3 days, and maybe testing and debugging +1 day.
Proposals concealed
Current freelance projects in the category AI & Machine Learning
Looking to find talented individuals for supporting the build up a tech start up with following skills: Machine learning and AI Databases UI/UX design Back and front end development Solutions architecture Graphical designs Software product management
Good day! Two tasks need to be completed: 1. Develop a product parser from an external website (10–40 thousand items, marketplace) with structured data saved in MySQL for subsequent output in WordPress. 2. Install and configure n8n on VPS, as well as organize AI content processing: prompt setup, text rewriting, image processing, SEO optimization, and text checking for AI detection. You can estimate the cost of completing both the entire project and each task separately. .
Task: one dashboard with all business metrics — advertising, funnel, payments, manager performance, revenue planning. Data is pulled automatically via API. Scope: only the YCL direction (employment in Europe). Kommo has other directions — only YCL funnel deals will be included in the repository (filter by funnel/tag to be agreed upon).1. Data Sources (Integrations) Kommo CRM — leads, deals, funnel stages, responsible persons, sources, dates of transitions between stages (must keep history), reasons for refusals, custom deal fields (see point 2). Stripe — payments, amounts, statuses (success/failure/refund), linked to deals. Meta Ads — expenses, impressions, clicks, CPL, leads by campaigns (currently operational). Google Ads, Reddit Ads, LinkedIn Ads — planned; architecture — extensible connectors without core rework. SEO/organic— Google Search Console + GA4. Cross-link: traffic source → lead in Kommo → payment in Stripe (UTM, deal ID in Stripe metadata — propose the mechanism). 2. Mandatory Cuts (Deal Fields in Kommo) Each metric must be filtered/grouped by: Client Citizenship (Kenya, Nigeria, India, etc.). Residence Status: lives in their country / expat (already in Europe). These are two different segments with different cycles, conversion rates, and checks. Country of Placement / Service: Poland, Serbia, Slovakia, Germany (ZAV). Manager, team, traffic channel, period. If any fields are missing in Kommo — the executor indicates which fields need to be added, the client adds them.3. Funnel and Leading Indicators Data by funnel, for each stage — summary and leading metrics: Traffic → lead: leads, CPL by channels + day-to-day expense/click dynamics. Lead → qualification: conversion + first response speed, touches/calls to the manager per day, unanswered leads. Qualification → contract/invoice: conversion + sent offers, stalled deals (days in stage above norm). Invoice → payment: payments, average check + unpaid invoices, failed payments. Summary: revenue, ROMI by channels, run rate to monthly plan. 4. Deal Cycle Average and median lead → payment cycle (business benchmark ~4 weeks), cycle trend over time. Breakdown of cycle by stages (how many days a deal sits at each stage) — to see which stage is dragging. List of deals that have stalled at a stage longer than normal. Cycle breakdown by segments: citizenship, residence status, country of placement, manager. 5. Early Warning of Decline (Key Block) Since the cycle is ~4 weeks, today's leads = payments in a month. The system must: Compare leads/qualifications of the current week with the moving average (4 weeks) and issue an alert if there is a downward deviation: “leads -X%, with a 4-week cycle expect a payment decline in the week [date].” Build payment forecast for 4 weeks ahead from the current pipeline: deals at each stage × historical conversion of the stage × remaining cycle. Highlight in red weeks where the forecast is below plan — with time to react. 6. Additional Payments and Sales Planning In the Kommo deal card, the date and amount of the planned additional payment are stored. The system must: Collect a calendar of upcoming additional payments: total expected, by weeks/months. Highlight overdue additional payments (date passed, no payments in Stripe) — a separate list for follow-up. Calculate the monthly plan as: plan − already paid − scheduled additional payments = how many new sales are needed (in money and in deal units at average check). Weekly schedule: additional payments + forecast of new payments against the weekly plan. 7. Manager Performance Daily snapshot for each manager: touches/calls, conversations, sent offers, payments — for each day separately, with a chart over the period. Progress on personal plan compared to monthly pace (ahead / on pace / behind). Benchmarking with colleagues. 8. Visualization and Roles “Traffic lights” (green/yellow/red) for key metrics relative to norms/plans; progress scales; trend graphs; mobile adaptive. Roles: CEO — everything; COO — entire funnel and managers; team lead — their team; manager — their metrics and position relative to colleagues. 9. Reports and AI Automated reports on schedule (daily summary, weekly report) in the dashboard and/or messenger. Free-form queries (“how has CPL from Meta changed over 2 weeks?”) — LLM over the repository. Alerts in the red zone and according to the rules from points 5–6. 10. Technical Expectations and Staging Repository (PostgreSQL/BigQuery or equivalent) + ETL: Kommo webhooks + periodic synchronization (15–60 min). Frontend: custom or BI tool — propose with justification; requirements for roles, traffic lights, forecasts, and AI queries must be implementable. Stages: (1) audit and metrics map → (2) MVP: Kommo + Stripe + Meta, funnel, traffic lights, roles → (3) deal cycle, early warning, additional payments and plan → (4) SEO, AI reports, alerts → (5) new advertising channels. Payment is staged, with a demo for each stage. In the response, indicate: similar projects (end-to-end analytics), stack with justification, timeline and cost estimates by stages, monthly ownership cost (hosting, tokens, licenses).
Task: deploy an LLM service that knows all the company's documentation and answers questions from the sales department managers. Current situation: the client has independently assembled a prototype (a separate project with uploaded company information, hosted on a server), but the information from the database is not transmitted to the model — likely, there is an issue with the API. We will provide the code and access. The first step is an audit: fix the existing setup or justifiably rebuild from scratch. Required functionality: Upload all company documentation: description of each service, regulations, FAQ, pricing (all materials will be provided). Answers strictly based on the uploaded documents (RAG). The model does not invent facts; if the answer is not in the database — it honestly informs about it. Access for managers via a link (web interface), with authorization. Scenarios: the manager asks any question about the company's work; inserts the client's question "as is" and receives a ready answer for sending; finds the necessary regulation/report by request. Knowledge base updates without a developer (uploading files through the interface or a connected folder). English language. History of requests for quality control. Technical expectations: LLM via API (Claude/OpenAI — propose with a cost calculation for tokens), RAG pipeline (vector database, embeddings), hosting on our server or in the cloud, HTTPS. The architecture should allow for future connection of the assistant to the analytical data warehouse (parallel project). In the response, indicate: examples of similar RAG projects, stack, timeline, cost of work, and estimated monthly ownership cost (tokens + hosting).
Creative Marketer / Ad Campaign Creator for Merivy — an AI-powered platform for beauty & aesthetics businesses (with a mascot!) Who we are We're a small startup building Merivy — booking and client management software for aesthetic clinics, beauty salons, barbershops, and other appointment-based businesses. At the heart of the product lives Merv — our AI agent (and green hand-shaped mascot ) who helps owners run their business: he sets up bookings, manages services and schedules, answers questions, celebrates wins, and generally feels like a team member, not a chatbot. What we're looking for A creative person who can turn this into a campaign people actually remember. Our reference for energy and tone is the media presence of viktor ( meet viktor) — we're a very different product, but we love how they talk to their audience: bold, human, funny, zero corporate blah-blah. We don't want a copy. We want that level of craft, with our own voice. The message we need to land Merivy helps you manage your clients, keep them happy — and most importantly, keep them coming back. Merv is the face of that promise: the little green teammate who never forgets a client, a booking, or a birthday. What you'll create A campaign concept built around Merv as the brand character (his voice, personality, running jokes) Scripts / storyboards for short-form video ads (IG Reels, TikTok) aimed at salon & clinic owners Static ad creatives and hooks for paid social Messaging we can reuse on the landing page and in the product You're a great fit if You've built campaigns or content for SaaS, beauty, or local-business audiences You can show us one thing you made that a stranger would send to a friend You think in characters and stories, not just "features and benefits" To apply Send 2–3 examples of your work and one sentence: how would Merv introduce himself to a salon owner in an Instagram ad? That one sentence matters more than your CV.