We build AI agents that handle real work — following up on leads, answering support tickets, updating your CRM — without someone walking them through every step. Each agent connects to your existing tools and hands off to a person when something needs human judgment.
AI Agent Development Services for B2B Companies
Adoption jumped fast over the last two years. Large companies aren't testing AI agents on the side anymore — they're putting them into daily operations, and spending is growing to match.
McKinsey found that 88% of organizations now use AI in at least one part of the business. Deloitte expects half of companies already using generative AI to be running agentic AI pilots by 2027, up from a quarter in 2025 — the shift is from experimenting to operating.
Amazon, Microsoft, Google, and OpenAI have all shipped agent platforms for enterprise use — Bedrock Agents, Copilot Studio, and Operator among them. When companies at that scale build agent infrastructure, it's a sign the technology has moved past the experimental stage.
An AI agent is software that can plan, decide, and act — not just answer a question. Give it a goal like "follow up with every lead who hasn't booked a call" and it works through the steps on its own: checking your CRM, drafting a message, sending it, and logging the result.
It talks to customers and staff in plain language across chat, email, or voice, and it can trigger real actions in your systems, not just suggest them. If you want to see what one could handle in your business, we're happy to walk through it on a call.
Talk to us about your first AI agent
From the first conversation to ongoing support after launch, we handle the full build. Here's what's included at each stage.
Before we write any code, we map your workflows and figure out where an agent actually helps — and where it doesn't. You get a clear picture of scope, cost, and expected return before committing to a build.
These are the jobs we build agents for most often — the repetitive, high-volume work that eats staff time without needing much judgment.
Handles common questions any time of day, resolves what it can on the spot, and hands off anything complex to a person with full context attached.
Follows up with leads before they go cold, answers basic questions, and books the call when someone's ready — so your sales team spends time on people worth talking to.
Helps customers find what they're looking for through plain conversation, recovers abandoned carts, and suggests relevant add-ons without feeling like a pop-up ad.
Checks calendars, books the meeting, sends reminders, and handles reschedules, cutting out the back-and-forth emails.
Flags unusual transactions in real time and routes anything suspicious to a person for review, instead of relying on a static rules list.
Takes on the repetitive work — matching invoices, pulling data from documents, keeping two systems in sync — that nobody enjoys doing by hand.
The underlying technology is the same everywhere, but the right use case depends on the industry. Industry-specific agents are actually the fastest-growing part of this market, projected to grow at nearly 63% a year through 2030 well ahead of general-purpose agents.
In healthcare, agents help with scheduling, triage questions, and patient follow-up — the volume work that pulls staff away from patients. Every build follows HIPAA requirements from day one, not as an afterthought.
How We Build
From the first conversation to a live agent in production, here's what each stage actually involves.
We map the workflow you want automated, pick the right model for the job, and set clear success metrics before writing any code.
We build the agent's decision logic, connect it to the tools it needs, and ground its answers in your actual documentation.
We connect the agent to your CRM, databases, and messaging channels. For larger builds, multiple agents are coordinated to work together.
We stress-test the agent against edge cases, set up escalation to a human when needed, and lock down access controls before launch.
We deploy to production with monitoring in place, then stay on to handle updates, fix issues, and scale the agent as your needs grow.
How the AI Agent Build Process Works
Every package includes full code ownership, standard security guardrails, direct API integration, and complete documentation.
$4,500Fixed project scope
Best for automating one clear workflow, like after-hours support or lead qualification, where you want to see real results before going further.
$9,800Fixed project scope
Our most common build. Multiple agents working together across departments, synced with your CRM and other core systems.
$24,500+Tailored enterprise scope
Full-scale agent infrastructure for larger organizations, with custom model tuning, private cloud deployment, and compliance built in from the start.
Need something bigger, like a multi-agent system or an on-prem deployment? Talk to us about custom scope →
Straightforward Pricing for AI Agent Development
A chatbot answers questions from a script. An AI agent plans and acts: it breaks a goal into steps, decides what to do next, calls the tools it needs (like your CRM or calendar), and follows through without someone guiding each step. Chatbots respond. Agents complete the task.
We ground every answer in your own documentation instead of letting the model guess, validate every tool call before it runs, and add a self-check step that catches obvious errors early. For anything high-stakes, like refunds or account changes, the agent hands off to a person instead of acting alone.
You do, fully. Every prompt, integration, and line of orchestration code transfers to your own repository at delivery, along with documentation for your team. Your business data is never used to train any public model, and you're free to take the codebase to another team if you ever want to.
We're not locked into one vendor, and we don't push a single model because it's easier for us. Depending on what the task needs, speed, reasoning depth, or cost, we build with Claude, GPT-4o, DeepSeek, Llama, or Gemini, using production frameworks like LangGraph and CrewAI, or a lighter custom setup when that fits better.
A single-agent build for one clear workflow usually takes 4 to 6 weeks, covering design, testing, and launch. A multi-agent system with CRM integration, custom tuning, and full testing typically runs 6 to 10 weeks. You'll get a firm timeline after the scoping call, not before you sign anything.
Yes. We build direct connections to your CRM, internal databases, and the tools your team already uses, including older or custom-built systems that most off-the-shelf platforms can't touch. Running Salesforce, HubSpot, an internal SQL database, or something homegrown? We can usually connect it, and we'll tell you upfront if something isn't realistic.
We keep watching it. That means tracking response times and task completion rates, catching unusual behavior early, and handling model provider updates before they break anything. Every plan includes a support window after launch, and if something's off, you hear from us before your customers notice.
Book a scoping call. We'll walk through the workflow you want to automate, ask about the systems it needs to touch, and tell you honestly whether an agent is the right fit for the problem. You'll get a fixed-scope proposal and timeline within a couple of days.
Frequently Asked Questions About AI Agent Development
