Consultation on creating an AI agent to accelerate the resolution of routine tasks - 60 minutes

I already have a nearly ready solution for GPT agents for contracts and routine tasks, which can be quickly adapted to your logic and discussed now within the framework of the marketplace. ))

Regarding the 60 minutes - we will manage, during this time we can analyze the current agent, choose an architecture for more complex scenarios, and understand where just GPT is needed, and where an agent with memory, checks, roles, and integrations is required.

From experience, an important nuance is usually not in the chat itself, but in how the agent receives data, checks the result, and does not break the business process in edge cases.

Look, here’s the nuance - I would suggest starting not from the idea of the agent, but from the task map - which actions are repeated, where there are documents or tables, where a person makes a decision, and where a result check is needed.

> 1st question - which tasks after the contract do you want to assign to the agents first?
… > 2nd question - should the agent work only in chat or also with documents, tables, CRM, email, and dashboards?

Relevant examples from Ingello:
> https://business.ingello.com/vorfahr - automation and AI logic around business processes
> https://business.ingello.com/fractal - agent approach and complex workflows
> https://business.ingello.com/tts - practical implementation of AI in product tasks

Main landing page for the marketplace - https://systems-fl.ingello.com

In general, it’s fine to start with a consultation, so as not to build a spaceship where a good cart would suffice... although sometimes the cart does end up becoming a spaceship. =)

I am ready to conduct a consultation and provide a short implementation plan based on the results - what can be done quickly, what is better not to complicate, and where the agent will indeed save time.

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Hello! My name is Nikita. I have been implementing AI solutions in paid advertising and automating marketing processes for over 2 years, working with Google Ads, Meta Ads, and TikTok Ads.
✅What you get when working with me:
— AI-enhanced advertising strategy instead of chaotic launches
— automation of analytics and control over project economics
— systematic scaling based on data and AI tools
📈I work with projects of various scales and use AI for faster analysis of results, finding growth points, and optimizing advertising processes without unnecessary costs.
I am ready to discuss your tasks and offer a practical plan for implementing AI in your project's advertising.

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Artem, hello!

You have already created an agent for contracts — a good start. More complex tasks depend not on the prompt, but on the architecture: tool calling, routing between steps, error control, and where human confirmation is needed.

I build exactly such systems — here is a live example, research-agent on LangGraph: huggingface.co/spaces/BlankD1/research-agent

I propose not just a call, but a mini-project over 3 days:

Day 1 — you send the current agent and a list of tasks; I analyze: what is already good, where the weak spots are, what does not scale to more complex cases.
… Day 2 — a 60-minute consultation based on the analysis: architecture, integrations (tables, CRM, webhooks), where human control is needed.
Day 3 — I send a written action plan: what to implement yourself, what requires a developer, in what order.

You will come away not just with answers, but with a clear action plan.

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Good day, I would be happy to conduct a short consultation for you regarding the automation of business processes through AI agents.

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Good afternoon, Artyom! I work with AI agents based on Claude and GPT, including document automation, prompt chains, and multi-agent systems with API tools. I am familiar with this stack from the inside, understanding where a prompt is sufficient and where orchestration, memory, or external integrations are needed. In 60 minutes, we will discuss your specific tasks: we will define the architecture for each scenario and what exactly should be delegated to the agents. I am ready at a convenient time.

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Started working with AI even before it became mainstream - in 2023. Created quite complex things that I cannot write about publicly.

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Hello, Artem. We can talk, I have experience, there will be results, I will provide several options and the optimal one. Message me privately.

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You have already overcome the first barrier — contract automation is working. Now the question is how to transfer this approach to more complex processes, where logic branches, context from multiple sources is needed, or interaction between agents is required.

In 60 minutes, your questions will receive concrete answers: what architecture is optimal for each task (prompt chains, RAG with pgvector, multi-agent), where to use local models via Ollama, and where to use OpenAI/GPT-4o-mini, and how to build guardrails so that the agent does not generate garbage on complex inputs. We will analyze your real scenarios — and for each, we will determine the stack, data schema, and potential bottlenecks.

Practical experience in integrating LLM into production (Go + OpenAI + Whisper + ElevenLabs for a telecom project, RAG system on pgvector + Ollama + OpenRouter) allows us to provide advice not abstractly, but based on what actually works in real-world conditions.

Which complex tasks do you want to discuss first — and do you already have drafts of what the agent should look like?

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Hello. Are you planning to use separate GPT agents for these more complex tasks or one multifunctional chain?

I will clarify the deadlines and budget more precisely in personal correspondence.

1. I will analyze your routine tasks and determine which of them can be delegated to agents.
2. I will propose an architecture for more complex scenarios, including integration with your data.
3. I will provide step-by-step guidance on setting up and testing agents for these tasks.

Thank you for considering my proposal. I look forward to the opportunity to work with you!

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Scaling basic document automation to autonomous systems that handle complex business logic requires a clear separation of context, memory management, and integration of external tools. Over the past few years, I have implemented dozens of complex integrations and smart automation scenarios that independently handle nonlinear processes. During the consultation, we will thoroughly analyze your routine workflows, determine the optimal branching architecture of the systems, and choose a reliable stack for working with complex contexts. By the end of the meeting, you will have a ready-made step-by-step technical roadmap for implementing these solutions. What specific logic is currently causing the most difficulties?

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Good day! I create GPT agents for routine tasks myself — I was recently working on an agent that pulls data and fills out documents based on a template, so your case with contracts is familiar. During the consultation, we will calmly discuss which tasks are really worth delegating to the agent, where it might make mistakes, and how to structure the logic to avoid overpaying for tokens. Please briefly tell me what you want to delegate — I will take a look in advance so that we can discuss the matter in 60 minutes. I am available today or tomorrow.

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I have practical experience in creating AI agents based on LLMs — from simple bots for document automation to complex multi-agent systems with tools and API integrations. In particular, I have developed agents for automating routine business processes specifically based on GPT/Claude, so I understand both the capabilities and limitations of these solutions. I can conduct a consultation where we will analyze your tasks together and determine the optimal approach for delegating them to agents. I am ready to share real cases and practical recommendations regarding the architecture of agents tailored to specific needs.

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Good day! We have experience in developing AI agents for automating business processes of any complexity. During the consultation, we will analyze the architecture of your tasks, optimize prompts, and integrate with APIs for scaling solutions. I will help build the logic of the agents' work to delegate routine tasks as efficiently as possible.

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