Want to know which companies are leading AI agent development in 2026? This article covers the top 10 firms helping businesses improve automation, customer service, and decision-making with AI. Learn about their key services, real-world use cases, what they do best, and why startups and enterprises trust them. Looking for the right AI partner? Let’s explore these top companies.
The top AI agent development companies in the USA include Intuz, SoluLab, LeewayHertz, Deviniti, Master of Code, Markovate, Adept, Scale AI, Azumo, and Azilen Technologies. These firms specialize in autonomous AI agents, multi-agent systems, LLM orchestration, and workflow automation for industries including healthcare, finance, retail, and logistics.
Many of these firms also rank among the leading machine learning development companies — the discipline that underpins every agent’s reasoning and prediction capability.
Whether you’re an early-stage startup or an enterprise with legacy systems, these ten companies in the USA stand out for their technical depth, real-world results, and business-first approach.
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- The global AI agents market was valued at $7.63 billion in 2025 and is projected to reach $182.97 billion by 2033 at a CAGR of 49.6% — making this one of the fastest-growing segments in enterprise tech.
- 62% of companies investing in agentic AI expect more than 100% ROI, with an average anticipated return of 171%, making AI agent development one of the highest-ROI tech investments available right now.
- The top 10 AI agent development companies in the USA — including Intuz, LeewayHertz, SoluLab, Markovate, and Deviniti — span everything from AGI-style research agents to production-ready vertical automation across healthcare, logistics, finance, and legal.
- AI agent development costs range widely: from $8,000–$25,000 for a simple single-function agent to $80,000–$300,000+ for enterprise multi-agent systems with compliance, memory, and full integration requirements.
- Choosing the right AI development partner requires evaluating five critical factors: domain experience, agent architecture depth, integration capabilities, transparent pricing, and post-deployment support including model drift monitoring.
What Is AI Agent Development?
AI agent development is the process of designing, building, and deploying autonomous software systems that perceive inputs, reason over context, and take goal-directed actions without continuous human instruction.
Unlike traditional chatbots, AI agents can plan multi-step tasks, use external tools, access memory, and adapt behavior based on outcomes. Businesses use AI agents to automate customer service, sales workflows, data analysis, compliance monitoring, and operational decision-making.
Why AI Agents Matter in 2026
AI agents have moved from experimental to essential. In 2026, they’re no longer a future-facing concept — they’re actively reshaping how businesses operate, automate, and compete.
Here’s what the data shows:
The global AI agents market was valued at $7.63 billion in 2025 and is projected to reach $182.97 billion by 2033, growing at a CAGR of 49.6%. – Grand View Research
According to Gartner, 40% of enterprise applications will be integrated with task-specific AI agents by end of 2026, up from less than 5% in 2025. By 2035, agentic AI could drive 30% of all enterprise software revenue — surpassing $450 billion.
The ROI Case Is Strong 62% of companies investing in agentic AI expect more than 100% ROI, with an average anticipated return of 171% – DemandSage – AI Agents Market Size & Adoption
AI-driven automation has led to a 20% decrease in diagnostic errors in healthcare, a 25% reduction in customer service costs across industries, and a 30% reduction in energy consumption in smart infrastructure – DemandSage – AI Agents Statistics 2026
Top 10 AI Agent Development Companies in the USA
1. Intuz
Intuz is an AI-first development company based in US providing custom AI solutions, advanced AI agent development, machine learning development, AI app development, workflow or business process automation with very deep technical domain expertise.
They’ve worked with companies in healthcare, eCommerce, finance, EV, legal, logistics, and D2C brands to roll out solutions such as AI-powered sportswear platform, AI-enabled SaaS platform for case management, document summarisation & insight extraction bots, smart and secure energy solutions, AI-powered dynamic pricing application, and more.
What makes them especially appealing to SMBs is their technical in-depth AI first technical expertise—offering everything from strategy consulting, fine-tuned LLMs to no-code/low-code integrations with platforms like Zapier, Make, and n8n.
Clutch Rating: ★★★★★ 4.8/5 – View full client reviews on Clutch
Category:
- Custom AI/ML Development
- AI App Development,
- AI Agent Development
Latest Case Study
Sapient – Engineering Smart & Scalable Energy Solutions
Challenge
Sapient Industries needed a way to process massive telemetry data streams efficiently while making insights accessible to non-technical stakeholders. Manual analysis was slow and complex, delaying energy optimization decisions.
Solution
Intuz has built an AI agent that continuously analyzed high-frequency telemetry data and generated weekly operational and energy reports with clear, natural-language summaries. It provided intelligent, data-backed recommendations, enabling building managers — even without technical expertise — to quickly understand trends and make informed decisions on energy optimization.
| Details | Information |
|---|---|
| Hourly Rate | $40–$70 |
| Employees | 50 – 100 |
| Founded | 2008 |
| US Presence | San Ramon, CA, USA |
| Website | www.intuz.com |
| Best For | SMBs wanting fast, full-cycle AI builds |
| Why Choose | AI first approach, Rapid turnaround, Focus on business value |
| Industry Recognition & Awards | Top Generative AI Company 2024 -Clutch, Global Award Winner for Spring 2024 – Clutch |
2. Solulab
Solulab combines deep domain expertise in blockchain, mobile app development, and artificial intelligence to deliver intelligent automation across digital platforms. Their AI capabilities range from intent-detection chatbots to predictive models that can drive personalized user experiences or streamline backend workflows.
Startups and founders love working with Solulab because they’re pragmatic—they help launch functional MVPs fast and iterate based on real-world feedback. Their past projects include a smart travel concierge for a tourism startup, AI-driven nutrition coaches, and chatbot support systems for health apps.
Clutch Rating: ★★★★★ 4.9/5 – View full client reviews on Clutch
Category
- AI
- Blockchain
- Web3 Development
Latest Case Study
AI Agent for Travel Recommendations
Challenge
Renowned travel agency needed an intelligent solution to improve customer engagement by swiftly understanding users’ travel preferences and providing personalized recommendations, while seamlessly integrating with their booking system.
Solution
SoluLab built an AI agent using NLP and ML (leveraging ChatGPT-style tech) that comprehended user inputs, generated personalized travel options, recognized voice commands, and integrated with the booking system, thereby significantly improving response times and customer experience.
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| Details | Information |
|---|---|
| Hourly Rate | $25–$49 |
| Employees | 200–300 |
| Founded | 2014 |
| US Presence | New York & San Francisco |
| Website | solulab.com |
| Best For | Startups & founders building smart products |
| Why Choose | Startup-savvy, quick productization |
| Industry Recognition & Awards | GoodFirms Trusted Choice Award, GoodFirms “Best Company to Work With” Badge |
3. Deviniti
Deviniti is best known for helping large enterprises inject intelligence into their operations through AI-enhanced tools. With deep experience in Atlassian ecosystems, they focus on making business processes smarter—think ticket triaging agents, AI-based reporting assistants, or agents that suggest workflow improvements using behavioral data.
Their case studies span the finance, insurance, and public sector domains. For instance, one of their clients used AI agents to automate support ticket classification across 15 departments, reducing human workload by over 60%.
Clutch Rating: ★★★★★ 5/5 – View full client reviews on Clutch
Category
- Generative AI Development
Latest Case Study
AI Agent: A Smart Team Member in Customer Service at Crédit Agricole
Challenge
The bank had an ambitious goal of increasing active customers without expanding its customer service team. This growth led to a rise in complaint volume, and the team struggled with slow response times, incorrect document classification, manual processing of routine requests, and delayed case handling—all affecting efficiency and customer satisfaction.
Solution
Deviniti implemented an AI Agent integrated into Crédit Agricole’s after-sales systems to automate document analysis, classification, and response generation. The AI Agent—via modules like Extractor, Classifier, and Generator—enabled automatic handling of standard operations, structured customer data, and prepared ready-to-send responses, drastically reducing manual workload.
| Details | Information |
|---|---|
| Hourly Rate | $50–$99 |
| Employees | 250 – 299 |
| Founded | 2004 |
| US Presence | Poland |
| Website | deviniti.com |
| Best For | Enterprises with existing tech stacks |
| Why Choose | Seamless AI integration into current tools |
| Industry Recognition & Awards | Clutch’s Top-Performing B2B Partner in Poland for 2022, Atlassian ITSM Specialized Partner Badge (April 2023) |
4. LeewayHertz
LeewayHertz is a top-tier player in the AI agent development space, particularly known for its work with autonomous multi-agent systems and LLM orchestration. Their solutions are used for supply chain optimization, AI operations management, and agent-based decision-making in regulated environments.
They’ve served enterprise clients including Coca-Cola, P&G, and Siemens, helping them build intelligent solutions like maintenance assistants, voice-command work order tools, and smart analytics agents. Their strength lies in transforming large, static systems into dynamic, adaptive ecosystems.
Clutch Rating: ★★★★★ 4.7/5 – View full client reviews on Clutch
Category
- AI Development
- Blockchain
Latest Case Study
AI-powered Medical Agent for Streamlined Disease Diagnosis
Challenge
A healthcare provider needed a faster, more consistent way to analyze patient data and deliver timely, evidence-based diagnostic insights, as manual processes were slow and delayed treatment.
Solution
LeewayHertz built an AI-powered medical agent using advanced algorithms and NLP to process patient information in real time, interpret symptoms, and present clear, evidence-backed recommendations. This improved diagnostic speed, accuracy, and overall patient care efficiency.
| Details | Information |
|---|---|
| Hourly Rate | $50–$99 |
| Employees | 200–250 |
| Founded | 2007 |
| US Presence | San Francisco |
| Website | leewayhertz.com |
| Best For | Enterprises seeking advanced multi-agent AI |
| Why Choose | Future-ready AI with fast enterprise delivery |
| Industry Recognition & Awards | Gartner 2024 Hype Cycle (Generative AI), Forbes Top 10 AI Consulting Firms |
5. Master of Code
Master of Code specializes in intelligent conversational platforms that engage users in meaningful ways. Rather than basic chatbots, their AI agents deliver personalized, dynamic, and intent-aware interactions.
Their work includes AI agents for global retail chains, customer service assistants in luxury hospitality, and even banking bots trained on financial regulations. With a heavy focus on UX, they ensure conversations aren’t just automated—but enjoyable.
Clutch Rating: ★★★★★ 4.7/5 – View full client reviews on Clutch
Category
- AI Agent Development
- Generative AI
Latest Case Study
AI-powered Support Agent for Zipify
Challenge
Zipify faced a high volume of repetitive customer queries and lacked tools to analyze support performance, slowing resolution times and impacting efficiency.
Solution
Master of Code built a custom AI agent integrated with Intercom to deliver contextual answers, summarize past interactions, and auto-generate help articles. An analytics dashboard provided real-time insights into response times, resolution rates, and agent workload, streamlining support operations.
| Details | Information |
|---|---|
| Hourly Rate | $50–$99 |
| Employees | 200 – 250 |
| Founded | 2004 |
| US Presence | New York & Los Angeles (Remote-enabled) |
| Website | masterofcode.com |
| Best For | Customer support & service automation |
| Why Choose | Engaging, NLP-rich conversational agents |
| Industry Recognition & Awards | Clutch Top 10 Chatbot Development Companies, GoodFirms Top Chatbot Development Companies |
6. Markovate
Markovate is a nimble team focused on delivering measurable business value through AI. They’re best suited for companies that want to experiment quickly with minimal risk—offering everything from AI-driven dashboards to process automation agents and email summarizers.
Their clients often include SaaS firms, healthcare providers, and logistics players who want low-complexity, low-cost automation tools that solve real issues like time delays, manual reporting, or data overload.
Clutch Rating: ★★★★★ 5/5 – View full client reviews on Clutch
Category
- Generative AI
- AI Agent
Latest Case Study
Legal AI Agent – LegalAlly
Challenge
A law firm needed a faster, more accurate way to handle legal research, document drafting, and compliance monitoring, as manual processes were slow and error-prone.
Solution
Markovate built LegalAlly, an AI agent powered by ChatGPT-4, to automate legal research, generate documents, and provide compliance insights. It also offered predictive analytics, conversational AI consultations, and robust data security, boosting efficiency and accuracy.
| Details | Information |
|---|---|
| Hourly Rate | $50–$90 |
| Employees | 200–249 |
| Founded | 2015 |
| US Presence | San Francisco , CA |
| Website | markovate.com |
| Best For | Mid-sized firms and MVPs |
| Why Choose | Fast, efficient AI for real business needs |
| Industry Recognition & Awards | Trusted AI development firm, as acknowledged by Clutch, AppFuture, UpCity |
7. Adept
Adept is at the cutting edge of AGI (Artificial General Intelligence), aiming to build AI agents that can operate any software tool a human can. These agents aren’t rules-based—they learn from usage, context, and trial-and-error.
Their flagship product, ACT–1, is being tested in environments like SaaS operations and enterprise data tooling. Although still early-stage, Adept is setting the foundation for AI agents that don’t just assist—but think and act.
Latest Case Study
AI Agent Dataset Creation
Challenge
Needed large-scale, high-quality interaction data to effectively train its action transformer model—but lacked the infrastructure and tooling to capture such telemetry at scale.
Solution
Adept partnered with SoftAge to develop and deploy a proprietary recording tool in just 15 days, then coordinated a team to generate approximately 4,000 hours of realistic user interaction data—empowering Adept.ai with the robust dataset it needed for rigorous model training and performance enhancement.
| Details | Information |
|---|---|
| Hourly Rate | $150–$300 |
| Employees | 51 – 200 |
| Founded | 2022 |
| US Presence | San Francisco |
| Website | adept.ai |
| Best For | Innovation teams & deep AI research |
| Why Choose | Pioneers in AGI-style adaptive agents |
| Industry Recognition & Awards | Listed among Forbes top 50 promising private AI companies, Fortune’s 50 AI Innovators 2023 |
8. Scale
Scale is the backbone behind some of the smartest AI agents today, supplying ultra-precise training data, RLHF pipelines, model validation, and security compliance. Their clients include OpenAI, Meta, and government defense agencies.
While they don’t build agents directly, no serious AI agent can perform without reliable data—and Scale makes sure that’s never the weak link.
Latest Case Study
Investment Management Agent
Challenge
Wealth managers and analysts relied on slow, manual processes—submitting requests to data teams, waiting for dashboards or queries, and manually interpreting results. This delay hindered real-time decision-making and reduced operational efficiency.
Solution
Scale’s AI agent uses natural language queries to instantly access portfolio data, generate visualizations, and provide actionable recommendations—automating document extraction and report creation for faster investment decision-making.
| Details | Information |
|---|---|
| Hourly Rate | $100–$200 |
| Employees | 501 – 1000 |
| Founded | 2016 |
| US Presence | San Francisco |
| Website | scale.com |
| Best For | Large-scale AI data & infra support |
| Why Choose | Best-in-class data for robust agent training |
| Industry Recognition & Awards | Forbes America’s Best Startup Employers 2025, Forbes Cloud‑100 (Top 10 cloud companies) 2024 |
9. Azumo
Azumo helps businesses modernize by embedding AI into existing software systems. They’re ideal for companies that have working platforms but want to upgrade with smart features—like email classification, customer support escalation, or operational automation.
A notable case is a real estate platform that used Azumo to create an AI agent that recommended ideal properties based on conversation logs with potential buyers.
Clutch Rating: ★★★★★ 4.9/5 – View full client reviews on Clutch
Category
- Generative AI
- AI Agent
Latest Case Study
Stock Market Alpha Predictor Agent (Stovell)
Challenge
Stovell needed a faster, AI-driven way to predict market reactions to price changes and optimize portfolios, as manual analysis slowed decision-making and limited returns.
Solution
Azumo built AI Agent that delivered dynamic pricing forecasts, portfolio optimization insights, and daily equity borrow rate predictions—integrated seamlessly with existing workflows.
| Details | Information |
|---|---|
| Hourly Rate | $25–$49 |
| Employees | 250 – 999 |
| Founded | 2016 |
| US Presence | San Francisco , CA |
| Website | azumo.com |
| Best For | System enhancement using AI |
| Why Choose | Easy AI integration with current tools |
| Industry Recognition & Awards | 2023: Top Rated AI Development Company by Clutch |
10. Azilen Technologies
Azilen builds production-ready AI agents that solve real-world problems in logistics, healthcare, and financial services. They’ve created smart claim processors for insurance, AI-enabled health assistants, and logistics bots that forecast demand and route loads efficiently.
Their focus is on reliability and cost control, making them ideal for companies that want AI benefits without complex overhead.
Clutch Rating: ★★★★★ 4.6/5 – View full client reviews on Clutch
Category
Enterprise AI Software Development
Latest Case Study
AI-Powered Talent Acquisition Agent
Challenge
The client needed a modern, AI-driven recruitment agent to improve employer branding, reduce bias, and streamline talent sourcing, as manual processes and legacy architecture slowed hiring.
Solution
Azilen built an AI-powered talent acquisition agent that automated recruitment workflows, enhanced candidate engagement, and delivered intelligent hiring insights—cutting cost per hire by 40% and increasing diversity hires by 34%.
| Details | Information |
|---|---|
| Hourly Rate | $25–$99 |
| Employees | 250 – 999 |
| Founded | 2009 |
| US Presence | Irving , TX |
| Website | azilen.com |
| Best For | AI in regulated industries |
| Why Choose | Balanced delivery across innovation & cost |
| Industry Recognition & Awards | Globee® Awards for Technology – Bronze Winner, Global Tech Awards – Excellence in HR Technology |
How to Choose the Right AI Agent Development Company
Not every AI development firm is the right fit for your project. Before you sign a contract, run through these five checks.
1. Domain experience
Ask for case studies from your industry — not close matches, actual ones. A firm that has built agents for logistics companies understands carrier integrations, shipment tracking, and real-time alerts in ways a generalist shop simply won’t. The same logic applies to healthcare, finance, or any regulated sector.
2. Agent architecture depth
There’s a big difference between a rule-based chatbot and a true AI agent that can plan across steps, use tools, and retain memory between sessions. Ask how they’d architect a solution for your use case. A firm that knows what they’re doing will walk you through it clearly — without buzzwords.
3. Integration capabilities
Your agent needs to connect to the systems your team already uses — your CRM, ERP, databases, and internal APIs. A good partner maps your existing stack before writing a single line of code, not after.
4. Pricing transparency
Custom AI agent development typically runs from $15,000 for a focused single-function agent to $300,000+ for complex enterprise builds. Ask what’s included in the build versus post-launch, and whether LLM usage costs (tokens, API calls) are factored in.
5. Post-deployment support
AI agents need ongoing attention — retraining as your data evolves, monitoring for failures, and updates as underlying models change. Ask specifically about SLAs, response times, and how they handle model drift after go-live.
How Much Does AI Agent Development Cost in 2026?
Cost is one of the first questions any business asks — and the honest answer is: it depends on what you’re actually building.
A simple single-function agent (say, one that auto-generates weekly reports from your data) is a very different scope from a multi-agent system that connects your CRM, ERP, and support tools and makes decisions autonomously across all three.
Here’s a practical breakdown:
| Agent Type | What It Typically Includes | Estimated Cost |
|---|---|---|
| Simple agent | 1–2 workflows, basic integrations, off-the-shelf LLM | $8,000 – $25,000 |
| Mid-complexity agent | 3–5 workflows, custom logic, CRM/API integrations | $25,000 – $80,000 |
| Enterprise multi-agent system | Multi-agent orchestration, memory, compliance, full integration | $80,000 – $300,000+ |
| Hourly (US-based firm) | Consulting, architecture, development | $40 – $150/hr |
| Maintenance retainer | Monitoring, retraining, updates post-launch | $500 – $3,000/month |
Quick Comparison: Best AI Agent Development Companies in the USA (2026)
| Company | Best For | Hourly Rate | Clutch Rating | Key Strength |
|---|---|---|---|---|
| Intuz | SMBs & full-cycle AI | $40–$70 | 4.8★ | AI-first, rapid delivery |
| SoluLab | Startups & MVPs | $25–$49 | 4.9★ | Fast productization |
| LeewayHertz | Enterprise multi-agent | $50–$99 | 4.7★ | LLM orchestration |
| Deviniti | Enterprise + Atlassian | $50–$99 | 5.0★ | Workflow intelligence |
| Master of Code | Conversational AI | $50–$99 | 4.7★ | NLP-rich UX |
| Markovate | Mid-market MVPs | $50–$90 | 5.0★ | Fast, low-risk AI |
| Adept | Deep AI research | $150–$300 | N/A | AGI-style agents |
| Scale AI | Data & infrastructure | $100–$200 | N/A | Training data pipelines |
| Azumo | System AI integration | $25–$49 | 4.9★ | Embedded AI upgrades |
| Azilen | Regulated industries | $25–$99 | 4.6★ | Compliance-safe AI |
FAQs
What makes an AI agent development company worth hiring?
The best AI agent development companies combine LLM expertise with real-world deployment experience. Look for firms with production-deployed agents (not just demos), industry-specific case studies with measurable outcomes, integration experience with your existing tech stack, and post-deployment monitoring capabilities. Clutch ratings and verified client reviews are reliable third-party validation signals.
How long does it take to build an AI agent?
It depends on what you’re building. A simple, single-function agent — say, one that auto-classifies incoming support tickets and routes them — can be ready in 3 to 6 weeks. A more complex agent that integrates with your CRM, ERP, and internal data systems, handles multiple workflows, and has compliance requirements built in will typically take 3 to 6 months from scoping to production deployment.
What are the predominant use cases for AI agents developed by USA-based leaders?
These firms specialize in building AI-powered chatbots, virtual assistants, workflow automation tools, and predictive analytics engines. Applications span customer support, IT automation, healthcare diagnostics, finance operations, defense surveillance, and e-commerce personalization. Their solutions consistently drive better user engagement, faster service response, and accurate, data-driven decision-making.
What sets US companies AI agent solutions apart in terms of scalability and integration?
US-based leaders design AI agents for secure, scalable deployment, capable of handling millions of annual interactions and data flows. Their platforms seamlessly integrate with enterprise CRMs, ERPs, cloud services, and third-party APIs. This ensures organizations can quickly expand automation across departments while maintaining robust compliance and operational efficiency.
How do top AI agent companies ensure ethical AI and data security in their solutions?
These companies adhere to strict data protection standards (such as GDPR, HIPAA, SOC 2), incorporate ethical AI frameworks, and emphasize transparency in model decisioning. Leading firms deploy robust monitoring, audit trails, and continuous learning mechanisms to reduce bias, ensure regulatory compliance, and protect sensitive information throughout the AI agent lifecycle
Do I need to replace my existing software to use AI agents?
No — and any firm worth working with will tell you the same. Good AI agents are built to work inside your existing stack, not replace it. They connect to the tools your team already uses through APIs and integrations. Whether that’s Salesforce, HubSpot, SAP, or a custom internal system, the agent plugs in and operates within your existing environment. You’re adding intelligence to what you already have, not starting over.
Which industries benefit most from AI agent development?
Right now, the clearest ROI is showing up in healthcare (patient scheduling, diagnostics support, records management), logistics and supply chain (shipment tracking, demand forecasting, route optimization), financial services (compliance monitoring, fraud detection, reporting automation), customer service (24/7 support, ticket routing, escalation handling), and legal (document review, research, contract analysis). That said, virtually any industry with repetitive decision-based workflows is a good candidate — the key is identifying where human time is being spent on tasks that follow a predictable pattern.
What tech stack do AI agent development companies typically use?
Most production-grade agents today are built on a combination of large language models (OpenAI GPT-4, Claude, or Llama for on-premise), orchestration frameworks like LangChain or CrewAI, vector databases for memory and retrieval (Pinecone, Weaviate, or pgvector), and cloud infrastructure on AWS, GCP, or Azure. The specific stack matters less than whether the firm can explain why they chose it for your use case — and whether it’s something your internal team can maintain after handover.
How much do AI agent development companies charge?
AI agent development costs range from $5,000 to $400,000+ depending on complexity. Simple chatbot agents: $3,500-$12,500 (2-6 weeks). Intermediate workflow agents with API integrations: $40,000-$70,000. Advanced autonomous multi-agent systems: $80,000-$120,000+. Initial development accounts for only 25-35% of 3-year total cost of ownership — budget for ongoing inference costs (15-25% of build cost annually) and model maintenance.
What should I look for in an AI agent development partner?
Evaluate on five criteria: (1) Production deployments — ask how many agents are running in production with real users, not just demos. 88% of AI agent projects fail before production. (2) Framework expertise — LangGraph, CrewAI, AutoGen, or proprietary frameworks. (3) Industry experience in your vertical. (4) Observability story — how do they monitor and debug agents in production? (5) Cost transparency — can they provide inference cost projections before you commit?
How long does it take to build an AI agent system?
Timelines vary by scope. A simple single-agent system (FAQ bot, document summarizer): 2-6 weeks. Multi-agent workflow with tool integrations: 2-4 months. Enterprise-grade autonomous agent platform with compliance, observability, and human-in-the-loop: 4-8 months. The biggest timeline variable is data quality — if your knowledge base needs cleaning, structuring, or enriching, add 2-6 weeks to any estimate.
