facebook meta pixel Experienced AI Agent Development Company - Inoxoft
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AI Agent Development Services
for Building Production-Grade
Autonomous Systems

Most AI agent projects take 12 months to prove what should take 12 weeks. We're an AI agent development company that builds production-grade agentic AI that integrates with your stack, ships with enterprise-grade guardrails, and earns measurable ROI in months. 

Our clients

AI Agent Development Services We Offer

Enterprise AI initiatives get split across consultants, builders, and integrators, and stall in the handoffs. Inoxoft delivers the end-to-end custom AI agent development services under one team: feasibility, design, build, integration, deployment, and optimization. 

AI Agent Consulting & Strategy 
We map your workflows, identify where agentic AI delivers measurable ROI, and design a phased roadmap with KPIs you can defend to the board. You walk away with a prioritized backlog, a target architecture, and a cost model
AI Agent Development
Inoxoft designs, builds, and deploys on the frameworks the production world actually runs on. Trained on your domain data, integrated with your enterprise systems, hardened for production from day one. 
AI Agent Modernization 
We modernize legacy conversational AI, rule-based bots, and first-generation LLM apps into autonomous agents with tool use, memory, multi-step reasoning, and the integrations the original system never had. Faster than starting over, safer than living with what's there. 
AI Agent Migration 
Inoxoft fine-tunes open-source LLMs on your proprietary data and builds RAG pipelines that ground agents in your knowledge base. The result: agents that answer with your terminology, your policies, and your facts, without leaking data to third-party APIs.
AI Agent Bug Fixing & Stabilization 

Connect agents to the systems where work actually happens.

When an agent loops, leaks data, ignores tool calls, misroutes tasks, or fails silently in edge cases, the cost compounds in real time. We audit the agent end-to-end and ship the fixes with regression tests, evals, and the observability needed to catch the next class of bug before users do.
Observability, Explainability & Hallucination Control 
Agents that drift, hallucinate, or output decisions no one can explain are agents your governance team will eventually pull. Inoxoft instrument agents with end-to-end tracing, evaluation pipelines, retrieval-grounded responses, citation enforcement, and hallucination detection.

Results Our Clients Achieve 

Up to 70%

of repetitive operations automated, freeing teams from clerical work and removing the headcount-scaling tax on growth

Up to 40%

reduction in operational costs through AI-driven workflow efficiency and fewer manual handoffs

2–3×

faster decision cycles, so agents pull, validate, and act on data in real time, replacing reports that took days

24/7

always-on customer and internal support with no proportional headcount growth

See what these numbers look like in your business

Tell us what you're trying to automate. We'll map your highest-ROI AI agent use case and give you an answer on whether to build it. 

Types of AI Agents
Inoxoft Builds

Different business problems need different agents. Across our custom AI agent development services, we build each one for a distinct workflow, integration depth, and decision boundary. 

Customer-Facing Agents 

Support teams drown in repetitive tickets while customers wait hours for answers that a knowledge base could already give. We build conversational agents for web, app, and voice that resolve 60–80% of inbound volume autonomously, take action in your systems (refunds, status updates, account changes), and escalate only when it actually matters. 

Sales & Lead-Generation Agents

Reps spend more time qualifying and enriching leads than closing them. Our agents score inbound against your ICP, enrich from public and CRM data, draft tailored outreach, and route only sales-ready leads to the right rep with full human-in-the-loop control where compliance requires it.

Data & Analytics Agents

Decision-makers wait days for reports that analysts have already run twice and trust the numbers less every time the dashboard changes. Inoxoft engineers agents that query your warehouse, BI stack, and operational systems in natural language and return decision-ready answers, with guardrails that make every metric traceable to its source query.

Internal Operations Agents

Multi-step internal processes sit in inboxes for days because no one owns the handoffs. The agents we ship coordinate across CRM, ERP, ticketing, and communication tools to execute these workflows end-to-end, without a human in the middle of every step.

Document & Knowledge Agents

Most enterprises hold thousands of contracts, claims, policies, and emails, and none of them are queryable or indexable. We design RAG pipelines tuned to your domain that extract the fields that matter, validate them against your rules, and trigger downstream actions in your terminology, not the model's. 

Compliance & Security Agents

Monitoring transactions and system events for risk is impossible at human speed. Our compliance agents flag, document, and report fraud, policy violations, and regulatory red flags in real time, with audit trails aligned to GDPR, HIPAA, SOC 2, and EU AI Act requirements out of the box.

Why Choose Our AI Agent
Development Services

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Up to 3× Lower Development Cost than Building From Scratch 

Most enterprise AI agent projects burn budget on infrastructure, MLOps tooling, and training pipelines that didn't need to be built. We start with pre-validated foundation models, reusable agent components from past production deployments, and custom ML training only where it actually moves accuracy. 

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Compliance-Ready from Day One 

AI governance is now a procurement conversation. Every agent we ship is engineered against the regulatory frameworks that regulated industries actually face. Audit-ready logs, role-based access, data residency controls, and explainability artifacts are part of the build.

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From Kickoff to Production in Weeks

Traditional enterprise AI projects take 9–12 months to reach production. Ours don't. We work in 1-week iterations, ship working agent components into staging from week one, and integrate with your CRM, ERP, and data infrastructure in parallel. The result: average integration timelines are roughly 40% faster than the industry baseline, with measurable user-facing value visible weeks ahead of typical enterprise rollouts.

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Agents Pre-Trained on Industry Data 

A foundation model trained on the open internet doesn't know your domain, but ours do. Every agent we deliver starts with industry-specific datasets curated from prior healthcare, fintech, logistics, and real estate deployments, then fine-tunes on your proprietary data and refines continuously through production feedback loops.

Let's talk about your AI agent

Bring us the workflow. We'll come back with a use-case map, a cost range, and a realistic timeline to production

Industries We Serve
Across AI Agent
Development Services

Our EdTech Success Cases

AI Energy Optimization: 20% Cost & Energy Savings

AI agent that monitors energy usage, analyzes patterns, identifies inefficiencies, and provides actionable recommendations for energy consumption optimization to reduce waste and carbon emissions.
Location:
The USA
Industries:
Manufacturing, Energy, Sustainability
Services:
Artificial Intelligence and Machine Learning, Data Analytics, Custom Software Development
Technologies:
Python, AWS, TensorFlow, Pandas
MacBook Experienced AI Agent Development CompanyPoster Video Web and Mobile Solutions For HR Management on Construction Sites

AI Pricing Agent: A 25% Rise in Property Sales

A sophisticated market analysis tool for real estate professionals constantly monitoring and analyzing real-time market feeds, including property listings, sales data, competitor pricing, and evolving market trends.
Location:
The USA
Industries:
Real Estate, Finance, Technology
Services:
Artificial Intelligence and Machine Learning, Data Analytics, Web Development
Technologies:
Python, Google Cloud Platform (GCP), Scikit-learn, Selenium
MacBook Experienced AI Agent Development CompanyPoster Video Scalable Platform for Data-Driven HR & Consultancy Services

AI Renewal Agent: 45% Stock Efficiency Increase

AI agent that analyzes historical sales data and predicts future demand with 90% accuracy to automate stock replenishment, ensuring optimal inventory levels and minimizing product outages and overstock.
Location:
The UK
Industries:
Retail, E-commerce, Supply Chain, Logistics
Services:
Artificial Intelligence and Machine Learning, Data Analytics, Supply Chain Management Software Development
Technologies:
Python, Azure, Pandas, ERP Integration API
MacBook Experienced AI Agent Development CompanyPoster Video Web Application for Shopify Wholesale Merchants

Let's talk about your AI agent

Bring us the workflow. We'll come back with a use-case map, a cost range, and a realistic timeline to production

Our AI Agent Development Process 

1. Business Framing & ROI Model
2. Data & Knowledge Audit
3. Architecture & Model Selection
4. Pilot with measurable KPIs
5. Production Deployment & Continuous Optimization
Business Framing & ROI Model

Find the use case worth building. Kill the ones that aren't.

We map your workflows, score candidate use cases against effort, impact, and risk, and build a defensible ROI model with the assumptions written down. The output is a prioritized backlog and a target architecture. If a use case can't carry its business case here, it won't carry it later either.

Risk reduced: building the wrong agent for the wrong workflow.

Data & Knowledge Audit

Most agents fail because of data, not models. We find that out before we build.

Inoxoft’s team audits the data and knowledge sources the agent will need, including coverage, quality, freshness, access patterns, and governance constraints. Where gaps exist, we surface them now and define the pipeline, retrieval strategy, and access controls to close them. Production-grade RAG, fine-tuning decisions, and compliance posture are all determined at this stage, not after deployment.

Risk reduced: an agent that hallucinates, leaks data, or can't answer the questions it was built for.

Architecture & Model Selection

We design the agent architecture (single-agent, multi-agent, hybrid), select foundation models against quality, latency, cost, and privacy requirements, and choose orchestration frameworks (LangGraph, CrewAI, AutoGen) on technical merit. Every choice is documented with the trade-offs and the migration path if the landscape shifts.

Risk reduced: vendor lock-in, model deprecation, or a stack that buckles when load goes up.

Pilot with measurable KPIs

Our team deploys a controlled pilot with real users, real data, and real workloads, measured against the KPIs defined in Stage 1. Guardrails, evaluation pipelines, and human-in-the-loop controls run from day one. If the agent doesn't hit the numbers, we adjust it here at this stage.

Risk reduced: a pilot that demos beautifully and breaks in production.

Production Deployment & Continuous Optimization

We deploy into your production environment with full observability, audit trails, and rollback paths. From there, we monitor performance, retrain on fresh data, tune guardrails as edge cases surface, and keep the stack aligned with evolving compliance requirements. Every agent we ship gets a feedback loop that makes it more accurate over time.

Risk reduced: drift, regression, compliance gaps, and the slow performance decay every production agent suffers without active maintenance.

Our tech capabilities

We Still Build
Custom Software
Just from 4x faster* now

*our R&D lab measured. Depends on the project complexity.

We embed AI directly into our engineering workflow, using Cursor and Anthropic Claude as fully integrated, secure tools. With senior engineers and strong delivery practices, we accelerate development while ensuring code quality, scalability, and compliance. The result: faster delivery, lower overhead, and production-ready solutions.

Web
Development

Build scalable, secure web platforms to handle your growth and outperform the competition with our custom software solutions.

Mobile Application
Development

Create high-performance iOS and Android apps that users enjoy using. We focus on mobile development that drives customer engagement.

Cross Platform App Development Services

Get to market faster with versatile apps that run seamlessly across all devices from a single codebase.

Quality
Assurance

Ensure your software works perfectly every time with rigorous testing. Our quality assurance team focuses on proactive bug prevention.

UI/UX
Design

Get intuitive interfaces that turn users into loyal customers. Our UX/UI design process ensures high customer satisfaction and captures investor attention

AI Agent
Development

Automate repetitive workflows with intelligent agents that think and act within your specific processes.

AI
Consulting

Stop the guesswork. We validate your data and find exactly where AI will deliver the fastest ROI.

Custom AI/ML Solutions

Build intelligence tailored to you with our custom programming company expertise. From predictive analytics to smart search engines that solve real problems.

Data Science and
Big Data Analytics

Turn your messy raw data into clear insights and actionable business moves using advanced data analytics.

Discovery
Phase

Test your idea before you build. We define the roadmap, technology stack, and features to ensure successful project outcomes

Technical
Audit

Find the bottlenecks. We review your legacy software and architecture to improve security, speed, and reliability.

IT
Security

Protect your revenue and reputation. We handle sensitive data with deep risk analysis and ironclad cybersecurity defenses

iOS App Development Services

Deliver premium, secure, and intuitive mobile experiences specifically for the Apple ecosystem.

Android Application Development Services

Reach a global audience with scalable and robust applications tailored for all Android devices.

How We Can
Cooperate with You

Product Development

Premium all-in software product creation

We provide complex custom software development services to build scalable solutions and secure enterprise ecosystems tailored to your unique workflows. We specialize in both web and mobile applications.

You Get

  • End-to-End Responsibility
  • Proactive Project Management
  • Trusted Tech Advisor
Team Extension

Classic outstaff model to work directly with best talent

Bridge skill gaps with senior talent — risk-free start, 1-day cancellation in the first 60 days, and free 2-week onboarding for any replacement.

You Get

  • Full flexibility — no long-term commitments
  • We cover onboarding time, so you don’t lose momentum
  • 75% higher developer retention
Dedicated Team

Gold standard of 2015-2024 software development
chosen by CTOs & Engineering

Get long-term engineering advisors who integrate deeply into your culture. Our dedicated team model scales perfectly with your roadmap.

You Get

  • Dedicated professional Project Manager
  • Predictable delivery powered by PMI Institute best practices
Zero-to-one delivery

Cutting edge AI approach to experience the full
benefits of AI

We turn your idea into a market-ready product, led by senior engineers using AI to deliver faster and smarter from day one.

You Get

  • Senior-led product ownership
  • Faster time-to-market
  • Scalable, well-structured architecture

    Let's talk about your product

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    Tetiana Banadyha
    Your first point of contact Tetiana Banadyha Business Development Manager LinkedIn

    Frequently Asked Questions

    How much does it cost to build an AI agent in 2026?

    The cost of AI agent development typically falls into three tiers:
    • Single-agent automations (one workflow, one integration): $25,000 – $75,000
    • Multi-agent systems (cross-system orchestration, custom RAG, fine-tuning): $80,000 – $250,000
    • Enterprise-scale agentic platforms (multi-agent orchestration, full observability, regulatory compliance, ongoing optimization): $250,000+

    How long does it take to build an AI agent and deploy it to production?

    Realistic timelines for production AI agents:
    • Single-agent MVP in pilot: 6–10 weeks
    • Production deployment with full integration: 3–5 months
    • Multi-agent system at enterprise scale: 5–8 months
    We work in 1-week iterations and ship working agent components into staging from week one. The most common reason projects miss this window is data preparation. We audit data readiness in week one, specifically to avoid that surprise in week ten.

    How do you prevent AI agent hallucinations in production?

    Hallucination control is a stack of techniques engineered together:
    • Retrieval-grounded generation (RAG): every answer ties back to a source document or database query
    • Citation enforcement: the agent surfaces its sources alongside the response, so users can verify
    • Constrained tool use: agents act only through pre-approved tool calls
    • Evaluation pipelines: we run accuracy and faithfulness benchmarks against real production traffic, continuously
    • Human-in-the-loop checkpoints: for high-stakes decisions (compliance, financial, clinical), the agent recommends, and a human approves
    • Drift detection: we monitor for accuracy degradation in production and retrain when it crosses a threshold

    What's the difference between an AI agent, a chatbot, and an AI assistant?

    The difference between an AI agent, a chatbot, and an AI assistant matters for procurement:
    • Chatbot: answers questions in natural language, usually from a fixed knowledge base.
    • AI assistant: answers questions and performs simple, single-step tasks when explicitly asked.
    • AI agent: plans and executes multi-step workflows autonomously, uses tools, retains memory across interactions, and makes decisions inside defined boundaries.

    Can our existing CRM, ERP, and internal tools integrate with custom AI agents?

    Yes. Production AI agents are only useful if they can read from and write to the systems where work actually happens. Integration depth is decided in the architecture stage based on your governance posture. The integration is engineered to be observable and reversible, so a misbehaving agent can be sandboxed without taking down the workflow.