WORKFLOX — USA

Custom AI Agent Development for US Startups and Enterprise Teams

Most US companies have already run the chatbot pilot. The question now is whether software can actually do the work — pull the record, make the decision, update the system, and hand a human the exception. That is what we build: autonomous agents with tools, memory, and guardrails that run inside your existing stack. We scope in days, ship in weeks, and price the whole thing up front in USD.

Why WORKFLOX

Why Businesses in USA Choose WORKFLOX

Agents that execute, not agents that chat

Every agent we ship has real tool access — CRM writes, API calls, database queries, ticket updates. If it cannot change the state of a system, it is a demo, and we do not bill for demos.

40-60% below US agency rates

US dev shops bill $150-350/hour for this work. We deliver the same production quality from Lahore at a fraction of that, with fixed-price scopes so you are never surprised by an invoice.

Real timezone overlap with EST and PST

Our team works a shifted schedule that gives you live hours with both coasts — standups with New York teams and afternoon calls with West Coast product leads, not overnight ticket ping-pong.

SOC 2-ready from the first commit

Audit logging, least-privilege service accounts, secrets management, and full action traces are built in, so your agent survives your security review instead of stalling in it.

USA Market

AI Agents Development Landscape in USA

The US is where agent budgets actually cleared procurement first — enterprise software spend here dwarfs every other market, and Salesforce, HubSpot, and Slack are the default operational backbone for a huge share of mid-market companies. That creates a specific opportunity: most US teams already have clean, API-accessible systems of record, which is exactly what an agent needs to act on. The constraint is engineering supply, not ambition — senior AI engineers in San Francisco, New York, Austin, and Boston are expensive and scarce, and hiring one takes a quarter. Meanwhile boards are asking for measurable operational leverage, not another pilot deck. That gap between mandate and capacity is why US companies increasingly bring in an outside build team that can go from scope to production inside one quarter.

Technology

Our Stack

We use proven, production-grade technologies — selected for performance, security, and maintainability.

OpenAI GPT-5
Claude Opus 4.5
LangGraph
OpenAI Agents SDK
Model Context Protocol (MCP)
Temporal
Pinecone
PostgreSQL + pgvector
AWS Bedrock
Salesforce API
HubSpot API
LangSmith

FAQ

Frequently Asked Questions

What is the difference between an AI agent and the chatbot we already have?

Your chatbot answers. An agent acts. A support chatbot tells a customer their refund policy; an agent checks the order in Shopify, validates it against policy, issues the refund in Stripe, updates the Zendesk ticket, and escalates the 8% of cases that fail validation. The build is harder because every action needs permissions, retries, and an audit trail — that is most of the engineering.

How much does a custom AI agent cost and how long does it take?

A focused single-workflow agent runs $6,500-16,000 and ships in 4-7 weeks. Multi-agent systems with several integrations land at $16,000-40,000 over 8-14 weeks. Enterprise programs with SSO, compliance review, and multi-environment deployment are $40,000-80,000+. Every engagement includes 60 days of post-launch bug-fix support at no extra cost.

Can our data stay in the United States?

Yes. We deploy to AWS us-east-1 or us-west-2 in your own account, and we can run entirely on Bedrock so no prompt or document leaves your AWS region. If you need stricter isolation, we will run open-weight models on your infrastructure instead — it costs more to operate but the data never leaves your perimeter.

What stops the agent from doing something expensive and wrong?

Scoped permissions, hard spend and rate limits, human approval gates on anything irreversible, and a full replayable action log. We define the blast radius before we write the agent loop. Realistically you should expect to keep a human in the approval path for the first few weeks of production while you watch the traces.


Other Locations

AI Agents Development in Other Markets

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