AI Agent Development Company
Autonomous · Multi-Agent · Reliable
Miracuves is an enterprise AI agent development company. We deploy high-performance cross-platform applications in 6 days using our curated base of 90+ white-label clone solutions - delivering 100% source code ownership with absolute IP safety on day one.
How Miracuves delivers AI agent systems - from 30+ deployments of real experience
After deploying 30+ production agent systems and processing millions of automated tasks, Miracuves has a specific way of building AI agents. We start from battle-tested agent architectures - already integrated with memory systems, tool APIs, guardrails, and monitoring - not from a blank notebook.
Our agent stack combines LangGraph for orchestration, AutoGen for multi-agent collaboration, and CrewAI for role-based task delegation. Every agent is built with ReAct reasoning, persistent memory (RAG + vector store), and built-in error recovery. One architecture, multiple deployment targets, full source code yours on handoff.
Who this service is built for: Engineering leaders and product teams automating customer support, data analysis, code review, sales outreach, research, or business workflows. Miracuves AI agent development fits when you want intelligent automation with published pricing, full IP ownership, and a company accountable for reliability - not individual contractors. If your task is purely deterministic (same inputs produce the same outputs every time), a simpler rule-based system may be more cost-effective. We will tell you before any commitment.
From our AI agent team - US eCommerce support system, 8 weeks
"Multi-agent support system processing 15,000+ monthly tickets across Zendesk, Slack, email, and live chat. We built three specialized agents - triage, search, escalation - orchestrated by a LangGraph supervisor. RAG knowledge base indexed 400+ product documents in Pinecone. Human-in-the-loop for refunds and cancellations. 85% auto-resolution from day one. Delivered week 8."
Why AI Agents at Miracuves
What Miracuves has built - what you can launch today
Generative AI
ChatGPT Clone
Fully functional AI assistant with deep chat context, prompt templates, API hooks.
Short Video
TikTok Clone
Scrollable short-video feeds, creator monetization, viral challenges, AI recommendations.
Ride-Hailing
Uber Clone App
Live GPS dispatch, real-time driver bidding, and dual passenger/driver interfaces.
Streaming
Netflix Clone
Video streaming platform with tiered subscriptions, user profiles, content library.
E-commerce
Amazon Clone
Multi-vendor marketplace with product catalog, cart, secure payments, reviews.
Super App
Gojek Clone
Modular architecture handles 20+ services in one app - rides, delivery, payments.
AI Agent vs Rule-Based Automation vs Generic LLM API - which is right?
Most AI companies pitch agents as the answer to everything. Miracuves compares honestly - your architecture choice determines reliability, cost, and maintenance.
| Metric | AI Agent · LangGraph ← MIRACUVES DEFAULT |
Rule-Based Automation | Generic LLM API |
|---|---|---|---|
| Autonomy Level | Full - tool use, planning, memory, self-correction | None - rigid if/then flows only | Architectureless - single-turn completions |
| Multi-Step Reasoning | Native - ReAct, reflection, sub-agent delegation | Linear - no branching intelligence | Manual - prompt engineering only |
| Tool Integration | 20+ pre-built tools, custom tool SDK | Pre-configured connectors only | None - raw API calls |
| Memory & Context | Persistent - RAG, vector store, session memory | No adaptive memory | Limited - context window only |
| Best For | Complex workflows · dynamic tasks · scale | Simple · predictable · high-volume | Single-turn · prototype · low cost |
Choose AI Agent if…
Your task requires multi-step reasoning, dynamic decision-making, or integration with multiple tools/APIs. You need memory, planning, and the ability to recover from errors autonomously.
Consider an alternative if…
Your workflow is entirely deterministic (same inputs = same outputs every time) or your budget cannot support LLM inference costs. See Python Automation →
How Miracuves engineers structure AI agent systems for production
These are the specific decisions our engineering team makes on every AI agent project - choices that determine whether a system scales, stays reliable, and maintains accuracy.
Architecture - Multi-Agent Supervisor Pattern
A supervisor agent orchestrates specialized worker agents via structured handoffs. Each worker owns a domain (search, code, data, email) with its own tools and memory. This is how Miracuves deploys a new agent workflow in 4 weeks without breaking existing operations.
Reasoning - ReAct with Reflection
Every agent uses the ReAct (Reasoning + Acting) loop with self-reflection. The agent thinks, acts, observes the result, and adjusts. The most common problem inherited from other builds: agents that hallucinate because they never validate tool outputs. We eliminate this with structured verification on every step.
Memory - RAG + Session + Entity Stores
Three-tier memory system: vector store (Pinecone/ChromaDB) for domain knowledge, session memory for conversation context, and entity store for persistent user/customer data. Every query is enriched before reaching the LLM.
What most AI agent builders get wrong
No error recovery in agent loops. No human-in-the-loop for critical decisions. Flat tool lists without prioritization. Single-agent for everything. Miracuves has inherited every one of these - correct architecture from day one is always faster than retrofitting reliability.
Three ways Miracuves delivers your AI agent project
Every engagement is with Miracuves as a company - a complete team, a defined process, and full delivery accountability. Choose the model that matches your project stage.
Readymade Clone · Fixed Price
White-Label Clone Delivery
Miracuves deploys a production-grade clone under your brand - iOS + Android + Admin Panel - in 6 days. Source code fully yours.
Custom Development · Scoped
Custom Agent Build
Miracuves builds from your specification - custom architecture, custom flows, unique features. Full team: engineer, backend, QA, PM.
Ongoing Retainer · Monthly
Ongoing Agent Development
Miracuves works as your ongoing development partner - new features, releases, maintenance on a monthly retainer with weekly sprint demos.
How Miracuves ensures every AI agent delivery meets production standard
Every project passes through Miracuves' quality gates before handoff - not as a checklist, as a non-negotiable delivery standard applied to every codebase we ship.
Our 6 Continuous Delivery Gateways
Every line of code, asset asset, and build profile must successfully clear all six quality control gates before repository handoff.
Code Review on Every Pull Request
Every line merged into your main branch is reviewed by a senior Miracuves engineer. No untested code reaches your production environment under any circumstances.
Automated Test Coverage Required
Unit tests for business logic, widget tests for UI components, and integration tests for critical user flows. Minimum coverage enforced before any release build is created.
Release Builds Profiled - Not Debug Builds
Miracuves profiles performance using agent profiling tools on every release build. Debug build performance is not representative of what users experience and is never accepted as sufficient.
Handoff Package - Not Just a Repository
Source code, documentation, environment setup guide, API documentation, deployment credentials, store credentials, and post-launch runbook - all included in every project handoff.
App Store Submission - Full Compliance Managed
Miracuves handles provisioning profiles, signing certificates, store listing creation, screenshot assets, compliance checks, and App Store review coordination for both iOS and Android.
Post-Launch Monitoring - 60-Day Active Support
Crashlytics and Firebase Analytics configured pre-launch. Miracuves monitors crash rates and performance metrics during the 60-day post-launch support window - proactive, not reactive.
The AI agent stack Miracuves ships with
Matched to your agent architecture and deployment requirements - not a one-size-fits-all default.
From brief to deployed AI agent - what happens and when
Every AI agent engagement follows the same delivery spine - whether you start from a readymade clone or a custom spec. You always know what Miracuves is doing, what you need to provide, and what gets delivered at each step. Timelines below reflect our standard clone sprint; custom builds run milestone-based with the same checkpoints.
Brief & NDA
Share your concept via WhatsApp. NDA signed same day. We ask 6 specific questions.
Scope & Plan
Right solution base, stack, and model confirmed. No payment before scope is agreed.
Build & Demo
Repo created, architecture set. First commit in 24h. Weekly working demo runs.
QA & Polish
Tested on real iOS/Android devices. Profiles optimized for Store guidelines.
Launch & Handoff
Full code and docs delivered. Store submissions handled. 60 days active support.
What AI agent development costs at Miracuves
We publish prices because we are confident in what we deliver. No "contact us for pricing" pages. No hidden fees after scope is agreed.
Readymade Clone
Fixed price · 6 day delivery · scoped
- AI agent system
- Admin panel included as standard
- Branding and white-label applied
- Full source code on handoff
- 60-day post-launch support
- NDA protected from day one
Custom Agent Build
Scoped before build · milestone billing
- Full AI agent team - engineer + backend + QA
- Custom architecture for your spec
- Weekly sprint demos - working software
- App Store and Play Store submission
- Full source code · complete IP transfer
- Milestone billing - no pay before delivery
Ongoing Development
Monthly retainer · cancel with 2 weeks notice
- Miracuves team assigned to your product
- New features, releases, and maintenance
- Weekly demos and sprint planning
- Direct communication - no relay
- Scales up or down as needed
- All code remains 100% yours
What affects AI agent project cost at Miracuves
Readymade clone pricing stays fixed when scope matches the base product. Custom Agent builds scale with: number of user roles (customer, driver, admin, vendor), real-time features (live GPS, chat, video), payment and compliance integrations (BaaS, KYC, multi-currency), multi-city or multi-language rollout, and third-party SDKs beyond the standard stack.
Typical AI agent budget ranges
Readymade clone: from $1,899 · 6 days.
Custom MVP: $8,000-$25,000 · 2-8 weeks depending on scope.
Ongoing retainer: from $2,299/month for feature work and maintenance.
Every quote is written before payment - no surprise invoices after kickoff.
The six days are ours, and they do not run past six. What can add time sits on your side: developer account verification, merchant onboarding and compliance approvals are controlled by the app stores and your payment provider, not by us. We list exactly what you need ready on the first call so you can start those in parallel.
What a real AI agent deployment looks like at Miracuves
A US-based eCommerce company needed an intelligent customer support system to handle 15,000+ monthly support tickets across email, chat, and phone - with 85% first-response automation and seamless human escalation.
The Challenge
Existing support team of 12 agents could not scale with growth. Average first response time was 4+ hours. Customer satisfaction scores were dropping. The client needed automation that actually understood context - not keyword-based chatbots.
What Miracuves Built
Deployed a multi-agent support system using LangGraph with three specialized agents: triage agent for intent classification, search agent for RAG-powered knowledge base retrieval, and escalation agent for human handoff. Built with 400+ product-specific knowledge documents indexed in Pinecone.
Outcome
85% of first-contact issues resolved without human intervention. Average first response time dropped from 4+ hours to 12 seconds. Human agents handle only 15% of tickets - the complex cases that require empathy and judgment. Customer satisfaction improved by 40%.
Client Testimonial
"We were drowning in support tickets. Every new hire meant weeks of training and they still struggled. Miracuves deployed a multi-agent support system that handled 85% of our volume from day one - order status, returns, shipping questions - all automated. The human escalation flow is seamless. Our support team now focuses on what matters: complex customer situations."
J.D., Head of Customer Experience
US eCommerce Platform · 15K Monthly Tickets
Project Brief
What clients say about Miracuves AI agent development
Across eCommerce support, sales automation, and data analytics projects - from mid-market to enterprise - verified on Clutch and Google.
Clutch · Customer Support Automation
"We deployed Miracuves' multi-agent support system across our eCommerce platform. The triage agent correctly classifies 97% of incoming tickets. Search agent pulls answers from 400+ knowledge docs in under 2 seconds. Escalation to humans is seamless. Customer satisfaction up 40% in two months."
Google Reviews · Sales Automation
"Our sales team was spending 60% of their time on lead qualification. Miracuves built a sales outreach agent that researches prospects, personalizes emails, and books meetings automatically. Our conversion rate improved 35% in the first quarter. The agent handles 500+ outreach sequences daily without errors."
Clutch · Data Analytics Platform
"Miracuves built a data analyst agent that connects to our Snowflake warehouse and generates weekly business reports automatically. Our BI team went from 15 hours per report to 15 minutes of review. The agent handles natural language queries - our product managers ask questions in plain English and get charts back."
Questions about AI agent development at Miracuves
What is the typical timeline for building an AI agent system?
A scoped single-agent deployment ships in 4-6 weeks: specification, architecture, tool integration, testing, and deployment. Multi-agent systems with orchestrators take 8-12 weeks. All timelines are stated in writing before any payment is requested.
Can AI agents integrate with my existing tools and APIs?
Yes. Miracuves builds custom tool integrations for any REST, GraphQL, or gRPC API. Standard connectors include Zendesk, Salesforce, HubSpot, Slack, Shopify, Snowflake, PostgreSQL, and custom internal tools. We add new tools as part of every agent delivery.
How do you ensure AI agents don't hallucinate or make mistakes?
Every agent uses structured verification: tool outputs are validated against schemas before being used, all critical actions require human-in-the-loop approval, and we enforce confidence thresholds. If an agent's confidence drops below 85%, it escalates to a human. RAG-based knowledge retrieval grounds every response in verified sources.
What LLM models do your agents use?
Agents support any LLM provider: OpenAI (GPT-4o, GPT-4-turbo), Anthropic (Claude 3.5 Sonnet), and open-source models via self-hosted endpoints. Miracuves recommends the model based on your latency, cost, and accuracy requirements - not a single default.
Can I switch between different LLM providers?
Yes. Miracuves builds with LangChain's model abstraction layer, so switching between OpenAI, Anthropic, or local models requires a configuration change - not a code rewrite. We benchmark and recommend the optimal model for your specific agent workload.
How does Miracuves handle data privacy and security for agents?
All agent data is encrypted at rest and in transit. Miracuves signs a bilateral NDA before any project details are shared. Agents can be deployed in your own VPC or cloud account. No training data leaves your environment. An IP assignment agreement confirming 100% ownership is signed at project start.
What happens when the LLM provider changes pricing or deprecates a model?
Miracuves monitors LLM provider changes and proactively migrates agents to equivalent or better models. The abstraction layer means swapping models does not require re-architecting your agent. Migration support is included in the 60-day post-deployment support window.
Do you provide ongoing support after the agent is deployed?
Every Miracuves delivery includes 60 days of post-launch technical support. Monitoring dashboards (Grafana + Prometheus) track agent accuracy, latency, and error rates. Bugs within scope are fixed at no cost. Monthly maintenance retainers are available at published rates for model updates, tool additions, and performance tuning.
Ready to build your AI agent with Miracuves?
Tell Miracuves what you are building. We will confirm the right solution base, service model, and delivery timeline - in writing, before any commitment is required from you.