Hire AI Agent Developers to ship production-grade AI Agents
Need to hire AI agent developers who ship real software, not demos? At Mobile Reality, our AI agent developers build autonomous agents that take action — not just answer questions. We combine expertise in OpenAI, Anthropic Claude, LangGraph, LangChain, and MCP with solid engineering experience to deliver production-ready AI agent development services for customer support, sales, and internal automation. Try our live agent on this page.
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AI Agent Development Services
Build autonomous AI agents that automate real work — customer support, sales qualification, internal workflows, code assistance, and more. Our AI agent development services ship production-grade AI agents with full observability, evaluation, and guardrails.
Modern AI agents go beyond chatbots and RAG pipelines. They plan, use tools, iterate on feedback, and execute real tasks against your APIs, databases, and SaaS systems. This unlocks automation and intelligent workflows that were impossible with prior AI generations — and it's why businesses now want to hire AI agent developers with real engineering experience.At Mobile Reality, our AI agent developers design and deliver agents on top of the best-in-class AI agent frameworks: OpenAI Assistants API, Anthropic Claude (with tool use and computer use), LangGraph for stateful multi-step workflows, LangChain for model and API integration, and MCP servers so agents plug into your existing stack.Most importantly, we ship production software — not prompts. That means observability with LangSmith or Langfuse, evaluation harnesses, prompt injection defense, cost caps, and regression tests for your AI project. The live agent demo at the top of this page is the same platform we deploy for clients.AI Agents in production
Leading businesses already run AI agents in production. Here are a few well-documented examples of intelligent agents at scale:Klarna publicly reported that its AI assistant — built with OpenAI — handled 2.3 million conversations in its first month, equivalent to the work of 700 full-time agents, with resolution times cut from 11 minutes to under 2. A clear case for intelligent automation.
Intercom's Fin AI agent resolves up to 50% of customer queries autonomously, with enterprise customers like Anthropic, Synthesia, and Monzo using these AI chatbots to reduce support load while keeping CSAT high.
Shopify Sidekick is a production AI-powered agent helping merchants run their stores — generating reports, editing products, answering questions — built into every Shopify admin as one of the clearest examples of intelligent systems in commerce.
GitHub Copilot's coding agent completes multi-step workflows in software engineering autonomously, demonstrating that AI agents scale from virtual assistants to full software-engineering collaborators across app development.
Technological benefits of our AI Agent development
Working with our AI Agent development team, you get more than a working prototype:
Observable and testable by default
Every tool call, every reasoning step, every token cost — instrumented with LangSmith or Langfuse so you can debug, evaluate, and improve each AI agent like any other production system. No black boxes, full visibility into every agent.
Guardrailed and cost-controlled
Input validation, prompt-injection defense, output filtering, retry limits, and hard cost caps. Our AI agent developers build in safety from day one, not as an afterthought. Critical for enterprise AI agent deployments.
Composable via MCP and tool interfaces
Agents connect to your real stack — Slack, Salesforce, Postgres, internal APIs — through Model Context Protocol (MCP) servers and typed tools. Clean separation between reasoning and action, with strong API integration across your existing software.
Model-agnostic agent architecture
Deploy on OpenAI, Anthropic, or open-weight models (including TensorFlow-based stacks). Our agent architecture expertise lets you swap providers without rewriting the application — no vendor lock-in, right skills applied from day one.
Objective advantages of AI Agents
The advantages of working with Mobile Reality on AI agents — for both product teams and end users.
Production-ready AI agent development01
Most AI agent projects stop at a Notion demo. Our expert AI agent developers ship agents with LangGraph state machines, evaluation harnesses, regression tests, cost monitoring, and CI pipelines — so what works on day one keeps working on day 180. That's the difference between a demo and a real AI project.
Own your data, models, and keys03
Deploy in your VPC, use your own API keys, retain full trace logs. Choose between Anthropic Claude, OpenAI, or open-weight models hosted where you need them. No forced vendor lock-in — a key benefit when you hire AI agent developers who build custom systems instead of reselling SaaS.
Battle-tested agent system development from our own platform05
Mobile Reality runs its own AI agent system in production — the live demo at the top of this page handles project estimation and sales flow for real inbound leads. Our AI agent developers bring the technical skills that work at scale, and the scars from the ones that didn't.
Agents that take real actions and automate workflows02
Our AI agents don't just chat — they query your databases, call your APIs, update tickets, draft messages, and execute multi-step workflows. Built on Model Context Protocol servers and typed tool interfaces, they integrate with the software you already run. True workflow automation, not another chatbot.
Cost-efficient custom AI agent development04
Off-the-shelf agent SaaS (Fin, Zendesk AI, Intercom) charges per resolution or per seat. A well-scoped custom AI agent development project — tuned for your domain, running on your account — typically lands 40-70% cheaper at scale, with better accuracy on your specific workflows.
Need a backend to run your agent stack? Pair AI agents with a Node.js backend, AWS infrastructure, or explore our broader AI automation services.
Matt Sadowski
CEO of Mobile Reality
Hire AI agent developers who ship production software
Partner with an AI agent development company that builds autonomous agents on your stack — not demos.
- Production-grade AI agent development with observability, guardrails, and evaluation.
- Multi-model orchestration via OpenRouter, LangGraph, and MCP integration.
- Autonomous AI agents that use tools, call your APIs, and automate real workflows.
- Own your data, models, and keys — deploy in your VPC, no vendor lock-in.
- Battle-tested from our own platform — the live agent on this page is built by the same team.
Our AI Agent Development Tech Stack
The tech stack behind every AI agent we ship. Our AI agent developers route requests through OpenRouter for model flexibility, orchestrate tools with typed interfaces, and instrument everything for production — the same architecture powering the live agent on this page.
OpenRouter Multi-Model Access01
We access OpenAI, Anthropic Claude, and open-source models through a single OpenRouter gateway, so each task runs on the right ai model instead of one vendor's default. This model-agnostic agent architecture lets us swap providers, compare openai models against open-weight alternatives, and control cost per request without rewriting the agent.
Model Roles & Smart Routing03
Not every step needs the biggest model. We assign roles — orchestrator, content writer, web-search, lightweight — and route each to a cost-appropriate model (for example GLM-5 for orchestration, Kimi K2 for writing, GPT-4.1-mini for quick calls). This routing is configuration, not hard-coded, giving a clean developer experience and fast iteration on prompt engineering.
MCP & API Integration05
Agents plug into your real stack through Model Context Protocol (MCP) servers and typed tool interfaces — Slack, Salesforce, Postgres, GitHub, and internal APIs. Clean separation between reasoning and action means our powered agents integrate with the software you already run, supporting agent collaboration across multiple systems.
Tool-Calling & Agent Orchestration02
Our agents are built around tool-calling orchestration: an orchestrator model plans the work, then delegates to typed tools — content generation, web search, database queries, and your APIs. This is how we turn a language model into an agent system that executes complex workflows and real tasks, not just chat. LangGraph drives stateful, multi-step agentic workflows.
Observability with Langfuse04
Every tool call, token cost, and reasoning step is traced with Langfuse, with per-session tags grouping all calls for one run in the OpenRouter dashboard. Combined with evaluation harnesses and regression tests, this gives us the capabilities to debug and improve each agent like any other production software — core to a reliable development workflow.
How We Build AI Agents — Our Development Process
A practical, repeatable step guide to our AI agent development process — the same workflow our AI agent developers follow on every AI project.
Every agent development process starts with scoping: we map the tasks the agent must handle, the tools and APIs it needs, and the success metrics. From there we design the agent architecture — which models fill which roles, how orchestration routes work between them, and where humans stay in the loop. This step guide keeps building agents grounded in real outcomes, not demos.Next comes implementation. We wire the orchestrator and its tools through OpenRouter, add web search and code generation where useful, and connect task tracking and data sources via MCP. Throughout, our AI experts apply prompt engineering, evaluation harnesses, and guardrails — prompt-injection defense, retry limits, and hard cost caps — so the agent system is safe before it ever touches production.Finally we ship and iterate. Agents go live with full observability, and we tune workflow automation, swap models, and refine prompts as configuration — no infra rewrites. The result is durable agents in software development and operations: powered agents that automate complex tasks, coordinate as multiple agents when needed, and keep delivering measurable value across projects.Hire AI Agent Developers
Our AI agent developers have shipped production systems on LangGraph, LangChain, OpenAI Assistants API, Anthropic Claude (with tool use and computer use), MCP servers, and Langfuse — with deep technical expertise and solid engineering experience. Whether you need a customer support chatbot, a sales copilot, internal ops automation, conversational agents for your product, or a multi-agent system with multiple agents coordinating, we deliver working software — not prompts. Hire AI agent developers who treat AI agent integration as real software engineering.
Business benefits for our clients
Why hiring production-minded AI agent developers gives you a competitive advantage:
24/7 customer support at a fraction of human cost
Autonomous agents resolve the majority of tier-1 support queries without human intervention, escalating only edge cases. Teams that deploy well-scoped support agents typically see 40-70% reduction in support cost while maintaining or improving CSAT.
Faster sales cycles
Agents can qualify leads, estimate project scope, draft proposals, and follow up — 24/7, in any timezone. Your sales team focuses on closing, not on chasing low-intent conversations.
Internal productivity gains
Internal knowledge-base copilots, code agents, and ops automation turn specialist work into accessible self-service — freeing your best engineers and operators from routine tasks.
Compliance and auditability
Every decision logged, every tool call traced, deterministic guardrails applied. Agents become easier to audit than human workflows, not harder — a real win for regulated industries.
Fast iteration without infra rewrites
Swap models, tweak prompts, add tools — without redeploying the underlying platform. Our agent architecture treats prompts and tools as configuration, not hard-coded assumptions.
Model-provider flexibility
Avoid vendor lock-in. Start on Anthropic, evaluate on OpenAI, move sensitive workflows to an open-weight model in your VPC — without rewriting the agent logic.
Why work with Mobile Reality?
On the market since 2016
Expert AI agent developers in LangGraph, LangChain, MCP and Claude
Owners and maintainers of Open Source projects available on GitHub
Experienced in working with a wide range of clients, from startups to enterprises
As an AI agent development company, Mobile Reality helps businesses go from idea to production-ready autonomous agents. We combine deep LLM expertise and architecture expertise with the software engineering discipline needed to ship AI systems that keep working after launch. Hire AI agent developers who align to your business goals, not framework fashion.
We use agile development methodologies to ensure our AI agent solutions are flexible, observable, and can respond quickly to changes in your business requirements. Our AI agent developers work fluently across LangGraph, LangChain, OpenAI Assistants API, Anthropic SDK, MCP servers, and Langfuse — with the right skills to select the best agent architecture for your AI project.
We take a collaborative approach to AI agent development, working closely with your team to scope, evaluate, and ship agents that deliver measurable business outcomes. Our AI agent developers and AI agent engineers deliver high-quality, observable, production-grade agents on time and within budget. The live demo on this page is proof we run what we build — this is agent consulting backed by real-world experience.
Frequently Asked Questions
Start your AI agent project today
Request a call today and get free consultation about your custom software solution with our specialists. First working demo just in 7 days from the project kick‑off.
Matt Sadowski
CEO of Mobile Reality
