We are a small AI consulting practice that helps financial services firms put AI to work inside their business. Our clients are owner-led firms like accountants, business appraisers, financial advisors, and insurance agents. We do not sell one-off scripts or disposable projects. We build practical AI systems that take real work off these firms' plates, delivered through ongoing monthly work. Demand is growing and the bottleneck is delivery. We are looking for one delivery partner to own that side of the work with us. How it works: we handle marketing, sales, and the paid advisory session that starts each client. Once a client moves to ongoing work, you take the lead on delivery. You build the systems against the priorities we set each month, and you run the weekly client meeting as their main point of contact. We stay in for support, to translate the client's business context, and to own the relationship at the top, but week to week the client works with you. What you would own: -Building AI and agentic systems for clients -Running the weekly client meeting and being the client's day-to-day contact -Taking each engagement from kickoff through delivery on the month's agreed hours, to a standard we can stand behind Compensation is $100/hour for your hours, which include both build time and client meetings. Straightforward and paid against tracked hours. As our client book grows, so do the hours available. Who we are looking for: -Genuinely fluent building real systems with modern AI tools. -Not just familiar with them. You should be comfortable architecting and shipping working systems for non-technical business owners. -Client-ready. You can run a working session, explain technical things plainly to a non-technical owner, and hold a client relationship week to week. -Native or fluent English. You are in front of clients every week, so clear, natural communication is non-negotiable. -Strong general technical judgment. The specific stack matters less than the ability to find the right solution and build it. -Reliable. We scope the work and stand behind it, so we need to count on what you deliver and how you handle the client. Who this is not for: anyone looking to own sales or pricing, anyone who only wants to build quietly and never talk to a client, and anyone new to this work hoping to learn on the job. To apply, tell us briefly: the most relevant AI system you have built and what it did for the business, how comfortable you are leading client calls, and how you approach building these systems. Start your reply with the word "Agentic" so we know you read this in full. Applications without it will not be reviewed. We will move quickly with the right person.

I am a partner at a recruiting firm seeking a conversational AI tool to enhance our communication with candidates and clients. Our business is highly conversational, and we primarily use LinkedIn and Loxo. We need a tool that can efficiently manage and personalize our interactions, potentially integrating with our existing platforms.

I'm an AI automation expert with a growing roster of clients, and I'm bringing on a skilled freelancer to help handle the smaller projects so I can keep up with demand. This isn't a new or one-off operation. I work with many clients already, and bring on new ones every week. I'm looking for someone reliable I can hand work to consistently, not just for a single project. You should be comfortable building AI automations independently and delivering clean, working solutions for client-facing work. To apply, please: - Send a short Loom introducing yourself - Share examples of your previous automation work I review every application personally, so a quick, genuine intro goes a long way. If we're a good fit, there's steady, ongoing work here.

I am looking for an experienced AI engineer to fix one critical issue in an existing AI agent. The AI agent is already built and working correctly in most workflow sections. It is a document processing and structured data extraction agent. The agent receives uploaded documents, analyzes the content, extracts required fields, validates the extracted information, and generates a structured final output for the application. However, there is one critical issue in the validation and final-output generation section of the workflow. In some cases, the agent marks the process as completed and returns a final result even when required extracted fields are missing or the validation step has failed. This causes the application to treat incomplete or invalid document data as successfully processed. This is not a full rebuild. I only need an experienced engineer to investigate the existing workflow, identify the root cause, and fix this specific issue. Detailed technical documentation is attached. Please review it before applying. Timeline: Urgent / start as soon as possible Please apply only if you have experience AI agents, LLM workflows, tool/function calling, validation logic, and state management.

We are seeking a highly experienced AI Solutions Architect / AI Agent Developer who has already built production-ready AI agents and can demonstrate previous work. The first engagement will be to provide a live demonstration of AI agents and discuss technical approaches for future client implementations. Successful candidates will become our preferred development partner for future AI projects.Required Experience You must have experience building AI agents using technologies such as: OpenAI APIs Anthropic Claude APIs Retrieval-Augmented Generation (RAG) LangChain or LangGraph Python n8n or Make.com Vector databases MCP (Model Context Protocol) integrations API integrations Microsoft 365 integration SharePoint integration Document automation OCR and PDF processing Database design Secure authentication and authorization Cloud deployment (Azure or AWS preferred)Preferred Experience Experience building AI solutions for: Law firms Construction companies Real estate Logistics and trucking Manufacturing Professional service firms Experience with document generation, contract review, client intake, workflow automation, dashboards, and internal knowledge assistants is highly desirable.Initial Engagement The first phase will include: A live demonstration of AI agents you have already built. Discussion of AI architecture and best practices. Review of our business model. Recommendations for building reusable AI frameworks for our clients. Technical planning for future projects.We value developers who: Think like business consultants, not just programmers. Communicate well with non-technical clients. Care about security and data privacy. Write clean, maintainable code. Can recommend the best technical approach rather than simply taking instructions. Are interested in building a long-term partnership.Please Include With Your Proposal A brief introduction about yourself. Links to AI projects you have built. A short video or live demo of an AI agent (preferred). Your favorite AI technology stack. Your availability. Your hourly rate. Your location and time zone. How many production AI agents you have successfully delivered. Why you believe you would be a good long-term partner.

We are seeking a senior AI developer to build and enhance AI models for our business. The role involves developing, testing, and deploying AI solutions, as well as improving existing models to increase accuracy and performance. The ideal candidate should have strong experience in AI development and be able to work independently on complex projects.

I need help with manychat automation. I've already started on the automation myself. I keep running into issues. I decided to look for an expert. The issues I'm running into - Chat is restarting when I've already had a conversation with customer. - Ai step doesn't start always start up to ask questions. - Since i'm hiring an expert i would like some more automation like follow ups and other ai steps. Other AI Steps - Once I manually reply have the ai pick up a keyword for example if they see "$" its knows an offer was sent. If they don't reply within 15 min ask Are you interested? then in another hour send a "?" for example -If offer is accepted have Ai step ask what day they are available. My flow is simple. Please see attached picture of the flow.

Overview We’re looking for an experienced AI engineer or AI systems builder to help us design and build an internal intelligence layer that turns fragmented customer data into actionable growth opportunities. Right now, customer insights live across multiple disconnected systems — CRM notes, product usage data, emails, support tickets, and spreadsheets. While the data exists, it is not structured in a way that helps us proactively identify expansion opportunities, churn risks, or account-level next steps. We want to build an AI-driven system that continuously synthesizes this information and helps our team understand: * What is happening inside each account * Where expansion or upsell opportunities exist * Which accounts are at risk and why * What the next best action should be for each customer ⸻ What You’ll Build You will design and implement an AI system that can: * Ingest structured and unstructured data (CRM, emails, notes, product signals) * Build dynamic “account intelligence profiles” for each customer * Identify patterns across accounts (usage drops, feature gaps, expansion signals) * Generate clear, human-readable account summaries * Recommend next-best-actions for sales, customer success, or leadership * Surface expansion opportunities based on behavioral and contextual signals * Flag risk signals early with supporting reasoning ⸻ Ideal Output For each account, the system should be able to generate: * A concise account narrative (“what’s going on here”) * Key signals and anomalies * Expansion opportunities (with rationale) * Risk factors (churn or stagnation indicators) * Suggested actions for the team this week * Confidence level and supporting evidence ⸻ Why This Matters We are sitting on a large amount of customer data, but most of it is passive. The goal is to turn it into an active intelligence system that helps our team: * Prioritize the right accounts * Increase expansion revenue * Reduce churn risk * Spend time on the highest-impact opportunities This becomes a core internal system that directly impacts revenue efficiency and customer outcomes. ⸻ Ideal Candidate We’re looking for someone with experience in: * LLM-based systems and agentic workflows * Data pipelines and multi-source data ingestion * Prompt engineering + structured reasoning systems * CRM systems (Salesforce, HubSpot, etc.) * Customer analytics / product analytics * Building internal AI tools or copilots * Backend + API integration work Bonus if you’ve worked on: * RevOps tooling * Customer success platforms * Data enrichment or account intelligence systems * SaaS growth analytics ⸻ Deliverables * System architecture for AI customer intelligence layer * Data ingestion and normalization approach * Prompting / reasoning framework for account analysis * Prototype system (or working MVP) * Output format for account intelligence reports * Documentation for internal expansion and scaling * Recommendations for tooling (build vs buy decisions) ⸻ Engagement This starts as a project-based build, but could expand into a long-term role as we scale the system across our entire customer base and additional workflows. ⸻ To Apply Please include: * Examples of AI systems or agentic workflows you’ve built * Experience integrating LLMs with real business data * Your recommended architecture for a system like this * Any clarifying questions you’d want answered before starting

I want to build a private multi-model RAG-based Opportunity Intelligence Agent. It should support document ingestion, opportunity-specific workspaces, vector search, source citations, multi-model routing across OpenAI, Claude, Perplexity, and possibly DeepSeek, and generate strategic recommendations from both uploaded files and live web research. This is intended to become a reusable base agent capable of knowledge retrieval, web research, multi-model orchestration, document analysis, citation generation, and agent clonding and configuration. It will be used for analyzing & strategy development for project opportunities, responding to RFPs, and proposal assistance, as well as other applications.

Build Private AI Chat Tool Using Anthropic Claude API — Law Firm Budget: $1,500–$3,000 fixed price Description: I'm a managing attorney at a small law firm in New York. I need a private, secure web application that gives my 4-person team access to Claude AI for document summarization and legal drafting — using the Anthropic API with Zero Data Retention so no client data is stored externally. What I need built: Browser-based chat interface (works like claude.ai but private) Per-user login (4 users) PDF upload — user uploads a document, selects a task (summarize medical records, extract key facts, etc.), Claude returns structured output Conversation history saved to our own encrypted database, tagged by case number Admin view where I can see all conversations across all users Hosted on a private server with HTTPS/SSL No data logged or stored outside our own database Clean, simple UI — non-technical staff must be able to use it Tech requirements: Anthropic Messages API (claude-sonnet-4-6) Zero Data Retention configured on the API account PostgreSQL or similar database for history Per-user authentication (JWT or similar) PDF text extraction before sending to API Encrypted database at rest You must have: Prior experience with the Anthropic Claude API specifically Experience building secure web apps with user auth and databases Portfolio or examples of similar builds Please answer this in your proposal: have you configured Zero Data Retention on the Anthropic API before? This is a fixed-price project. I own all code upon final payment.