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Designed in California

AI Agents Development

Custom AI Agents for Business

Autonomous agents powered by GPT-4o and Claude that handle sales, support, research, and operations - without human input.

Discuss Your Use CaseSee Pricing
  • $2kstarting price
  • GPT-4oClaude 4 · Gemini
  • 2–10 wksdelivery time
  • ∞tasks automated

Capabilities

Agent Use Cases We Build

If a task involves decisions, tools, and multiple steps - an agent can automate it.

  • Sales Agent

    Processes inbound leads, asks qualifying questions, fills CRM with complete data, and schedules follow-ups automatically - 24/7.

  • Support Agent

    Resolves customer issues autonomously - searches knowledge base, checks order status, processes returns, escalates only edge cases.

  • Analytics Agent

    Pulls data from multiple sources, identifies trends, generates formatted reports, and pushes insights to Slack or email on schedule.

  • HR Screening Agent

    Reads resumes, runs initial chat interviews, scores candidates against your criteria, and notifies hiring managers of top matches.

  • Content Agent

    Writes posts, adapts tone per platform, generates ideas from a content plan, and schedules publications automatically.

  • Operations Agent

    Coordinates tasks between teams, tracks deadlines, sends reminders, and generates progress reports without manual oversight.

Stack

Technology Stack

We use the most capable models and frameworks available - selected based on your cost, latency, and privacy requirements.

  • GPT-4o
  • Claude 4
  • Gemini 2.5
  • LangChain
  • LangGraph
  • OpenAI Assistants API
  • Pinecone
  • Weaviate
  • PostgreSQL
  • Redis
  • FastAPI
  • TypeScript

Standards

What Sets Our Agents Apart

  1. Tool use: search, APIs, databases, CRM - real actions, not just text

  2. Persistent memory across sessions via vector database

  3. Structured output: agents return data in schemas your systems expect

  4. Human-in-the-loop option for high-stakes decisions

  5. Multi-agent orchestration for complex parallel workflows

  6. Full observability: every reasoning step is logged and traceable

  7. Cost controls: token budgets and rate limits per task

  8. Incremental delivery - you test each capability before we extend

Case files

AI Agent Projects We Delivered

Autonomous agents running in production.

Sales

Lead qualification agent for a B2B SaaS - saved 15 hours per week

  1. Challenge

    A B2B SaaS company was receiving 200+ inbound leads per week. Sales reps spent 15 hours qualifying them manually - asking the same 8 questions over email, waiting for responses, then updating CRM.

  2. Solution

    AI sales agent that automatically sends personalized qualification emails, interprets free-form replies using GPT-4o, fills CRM fields, scores leads by fit, and assigns hot leads to the right rep with a summary.

  3. Result

    15 hours/week of manual work eliminated. Lead response time: from 8 hours to under 4 minutes. CRM data completeness improved from 40% to 96%.

Analytics

Analytics reporting agent for a fintech - 6 hours to 4 minutes

  1. Challenge

    The growth team at a fintech company spent 6 hours every Monday morning pulling data from 5 different sources (Mixpanel, Stripe, PostgreSQL, Google Ads, HubSpot) and assembling a weekly report.

  2. Solution

    Autonomous analytics agent that runs every Monday at 7AM: pulls data from all 5 sources, calculates KPIs, identifies anomalies, writes a narrative summary, and posts the formatted report to Slack.

  3. Result

    Monday report time: 6 hours → 4 minutes. Report is ready before the team starts work. Analyst now focuses on interpretation, not data collection.

HR

CV screening agent for a high-volume recruiter - 300 CVs in 40 minutes

  1. Challenge

    A recruitment firm processing 300 CVs per week for 12 active job positions. Screeners spent 3 hours per position just doing first-pass filtering before any qualified review.

  2. Solution

    Multi-step agent pipeline: reads each CV, extracts structured data (experience, skills, education), scores against job requirements, flags red/green/yellow candidates, and generates a ranked shortlist with reasoning.

  3. Result

    300 CVs screened in 40 minutes vs. 36 hours manually. Top-10 shortlist accuracy: 88% match with what senior recruiters would have selected. Time-to-first-interview cut by 5 days.

Configurations

Pricing

Priced by scope of tools, integrations, and reasoning complexity.

Single-Task Agent

from $2,000

2–4 weeks

  • One focused task (e.g. lead qualification)
  • 1–2 tool integrations
  • Basic memory (conversation context)
  • Telegram / Slack / API delivery
  • 30-day post-launch support
Get Started
★ Most Popular

Business Agent

from $8,000

6–10 weeks

  • Multi-step workflow automation
  • CRM, email, calendar integrations
  • Long-term memory with vector DB
  • Admin dashboard for monitoring
  • 3 months of support included
Get Started

Multi-Agent System

from $15,000

2–4 months

  • Multiple agents collaborating on tasks
  • Orchestrator + specialist agent architecture
  • Custom tool library and API gateway
  • Full observability and cost analytics
  • 6 months of support included
Start a project

Protocol

How We Build AI Agents

  1. 3–5 days

    Workflow Mapping

    We document the exact task sequence, decision points, tools needed, and edge cases before writing a single line of code.

  2. 1–2 weeks

    Prototype

    A minimal working agent on the real data. You interact with it and give feedback before we build out the full system.

  3. 2–8 weeks

    Build & Integrate

    Full agent with all tools, memory, and integrations. Each integration is tested against real production data.

  4. Ongoing

    Monitor & Tune

    Post-launch monitoring dashboard, cost tracking, and regular fine-tuning based on real usage patterns.

// What's open, what's sealed

Your project stays yours

No two briefs are alike - the requirements never are - so we design for yours instead of assembling from templates. Your names, architecture and numbers stay yours: an NDA is our default, not an exception. Send us yours before the first technical call and we will sign it.

ai.aunimeda.com
AUNI-01LIVE
Sync 100%
AI Orchestration

Auni AI

An orchestration layer over Aunimeda's own models - Auni-1, Auni-2 and Auni-3 - deployed across industries: sales conversations, answers from a company's own knowledge, voice agents that take the call and carry out actions.

AUNI-02LIVE
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Drawing Engine & App

AuniDraw

A drawing app on our own low-latency engine in C++ and Dart: pressure-sensitive stylus input, brush compositing, one canvas on iOS and Android. Free - for children discovering how to create and for professionals.

AUNI-03LIVE
Sync 100%
Business System

Aunimeda CRM

Everything a business actually runs on, in one place: clients, orders, inventory, staff and the numbers that show how it is going.

ARCHIVEOpen
Sync 100%
Client Work

Client Projects

Websites and systems we build for clients. The ones we can show - with the client's written consent - are in our portfolio.

NDA-███SEALED
Encrypted
Client Systems

Under NDA

Work delivered under non-disclosure. Names, architecture and numbers stay with the client.

01 / 05Auni AI
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Query log

Frequently Asked Questions

What is an AI agent and how is it different from a chatbot?

A chatbot follows a pre-written script and can only respond to questions it was programmed for. An AI agent is autonomous - it can reason through multi-step tasks, use external tools (search, APIs, databases, CRM), execute actions, and adapt to any situation. A sales agent, for example, can receive a lead, look up company info, check CRM history, draft a personalized email, and schedule a follow-up - all without human input.

How much does AI agent development cost?

A basic single-purpose agent (one task, one integration) starts from $2,000. A business agent with multiple tools, memory, and CRM integration costs $4,000–$8,000. A multi-agent system where agents collaborate on complex workflows starts from $15,000. Pricing depends on number of tools integrated, complexity of reasoning chains, and backend infrastructure required.

What AI models do you use to build agents?

We use OpenAI GPT-4o, Anthropic Claude 4, and Gemini 2.5 as the reasoning backbone. For orchestration we use LangChain, LangGraph, and custom agent frameworks. For memory we implement vector databases (Pinecone, Weaviate) and PostgreSQL for persistent state. Model selection depends on your cost targets, latency requirements, and data privacy constraints.

What tasks can an AI agent automate?

AI agents excel at: lead qualification and CRM data entry, customer support with autonomous resolution, content creation and scheduling, data research and report generation, HR screening and interview scheduling, e-commerce order management, and multi-step API orchestration. If a task involves decision-making, tool use, and multiple steps - an agent can handle it.

How long does it take to build a custom AI agent?

A focused single-task agent takes 2–4 weeks. A full business agent with multiple tools, memory, and integrations takes 6–10 weeks. A multi-agent system takes 2–4 months. We start with a discovery phase to map out the exact workflow, tools needed, and edge cases - this saves time during development and ensures the agent does exactly what you need.

Next step

Ready to Automate with AI?

Describe your workflow and we'll tell you exactly what an agent can automate - a 30-minute scoping call.

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