How long does AI agent development take from kickoff to production?

A single agent reaches a working prototype on your real data in about 14 days and guarded production in six to eight weeks. Our pricing agent went live in six weeks and the return-scoring agent in four. Multi-agent layers typically run three to four months, mostly because of integrations and approvals.

How much does an AI agent development company charge mid-sized businesses?

Our engagements start at $15,000+ for a two-week agent prototype, $45,000+ for a production agent integrated with one system of record and $75,000+ for a multi-agent operations layer. Published client builds on this site ran $55,000 and $72,000. You get a fixed scope after the free audit.

Do we own the agent code, or is it licensed?

You own it outright: the repository, prompts, orchestration logic, evaluation harness and every integration we write. There is no proprietary agent platform underneath and no per-seat license that grows with your headcount, so you can take the build in-house after handover.

Is our company data safe when AI agents act on it?

Every agent runs inside your private cloud perimeter, not ours. Documents, pricing, supplier terms and customer records never leave your environment and never train a public model. We log every agent action for audit and put a human approval gate on any decision with financial or legal consequences.

Can AI agents integrate with our existing ERP and CRM?

Yes, and that is usually the hard half of the project. We integrate with SAP Business Network, Coupa, Jaggaer, NetSuite, Shopify Plus, Amazon Seller Central and Magento, plus legacy ERPs over their own APIs. Where a system has no usable API, we build the extraction layer instead.

What happens after launch, and how do we measure results?

We measure accuracy, hours saved, error rates and business outcomes such as margin or fraud against your pre-launch baseline. At handover you get code, documentation, the evaluation harness and runbooks. You can run agents in-house or keep us while autonomy expands. There is no mandatory retainer.

AI Agent Development Company for Agentic Workflows

Your team is buried in multi-step manual work, and most agentic AI companies want a six-figure platform contract first. As an AI agent development company, we build agents that plan, call your systems and act on your data behind approval gates, with a working prototype guaranteed in 14 days.

How an AI Agent Earns Its Autonomy

Agents start supervised and earn autonomy step by step, as measured accuracy proves they can handle a decision on their own.

― HYBRID BUILD

Agents Where They Belong, Code Everywhere Else

Agentic AI means software that plans and executes a multi-step task, not a chatbot. But not every step needs an LLM. Money movement, compliance checks and integrations run on classic, tested code; agents handle judgment on messy inputs; approval queues ship on low-code.

― TRACK RECORD

AI Agents Already Running in Production

Our self-healing pricing agent lifted retained margin 12% and cut repricing latency to under an hour, live in six weeks. A return-scoring agent cut fraudulent returns 38% (representative engagement, NDA), and a site-selection agent analyzed 8,500 reviews. Explore our case studies.

Explore our case studies

Your Data Stays Yours

Every agent runs inside your private cloud perimeter under SOC2/GDPR-aligned practices. Documents, pricing and customer records never leave your control and never train a public model.

You Own the Agents

You own the repository, prompts, orchestration logic, evaluation harness and every integration. No proprietary agent platform or per-seat license stops you from taking the build in-house.

Evaluation Before Autonomy

Each agent ships with an evaluation harness that scores it on your real historical cases, so autonomy expands only when the measured numbers clearly justify it.

Every Action Logged

Agents log each decision, tool call and data source, so your team can audit what happened, roll back mistakes and explain outcomes to customers or regulators.

AI Agent Development Cost & Packages

Agent Prototype

$15,000+

One agent, one workflow, built and validated on your real data in about two weeks. The right entry point when you need proof that an AI agent works on your documents before committing a larger budget.

What's included?

Scope & Architecture: one session to pick the highest-value agent workflow

Agent Build: functional agent on your real data, not a scripted demo

Stack Setup: Python, FastAPI and agent framework foundation ready to extend

Findings Report: measured accuracy, failure modes and the fastest path to production

Book a Free Agent Workflow Audit

Production Agent

$45,000+

A single agent hardened for daily production use, integrated with one system of record and deployed in your private cloud with monitoring and approval gates. This is the tier most mid-market operations teams start with.

What's included?

Everything in Agent Prototype: rebuilt on production rails for real daily volume

Integration: secure API connection to one ERP, CRM or storefront

Guardrails: approval queues, retries, fallbacks and an evaluation harness

Scaling Roadmap: a prioritized plan for the next two agent workflows

Book a Free Agent Workflow Audit

Agentic Operations

$75,000+

A multi-agent layer spanning several workflows and systems, with orchestration, shared memory and human-in-the-loop governance across the chain. Built for teams replacing a genuine operational bottleneck, not testing an idea.

What's included?

Everything in Production Agent: extended across multiple connected agent workflows

Multi-System Integration: SAP, Coupa, NetSuite, Shopify Plus and legacy ERPs

Compliance: SOC2/GDPR-aligned deployment inside your own perimeter

Team Training: runbooks and hands-on onboarding so your team operates it

Book a Free Agent Workflow Audit

Why Choose Building Agentic?

Most agentic AI companies sell a platform license or a sandbox pilot. You could also hire a freelancer, or work with one accountable engineering team.

The Right Hammer

We pick classic engineering, LLM agents or low-code per component, so you pay for reliability where it matters and speed where it does not.

Production From Day One

Your prototype runs on the architecture that carries into production, so a validated agent scales instead of being rebuilt from scratch.

Priced for Mid-Market

Engagements start at $15,000 and land in weeks, not the six-figure multi-quarter rollouts enterprise agent vendors quote by default.

You Own the Code

No proprietary agent platform, per-seat license or subscription stands between your team and the agents after handover.

How It Works

Building AI agents with us follows the same four-stage rhythm whether you run a 30-person operations team or a division inside a larger company: fast enough to prove value this quarter, disciplined enough to hand over.

Step 1

Audit the Workflow

We map your process end to end and find the single decision loop an agent can own first, ranked by recoverable cost.

Step 2

Build the Agent

A working agent goes live on your real data within about two weeks, wired to your systems rather than a sandbox copy.

Step 3

Harden & Deploy

We add guardrails, evaluations and monitoring, then deploy inside your private cloud with approval gates your team controls from day one.

Step 4

Expand Autonomy

The agent earns more autonomy as measured accuracy justifies it, and you get a roadmap for the next workflows worth automating.

Industries We Build AI Agents For

AI agents pay back fastest where high-frequency, low-value decisions eat your team's week. These are the operational areas where we already run production agents for US mid-market companies.

Procurement and supply chain teams automating RFP intake, supplier checks and tail spend.

See our Procurement & Supply Chain AI work

Finance teams putting invoice capture, matching and exception handling on autopilot.

See our Invoice & AP Automation work

E-commerce and retail brands running pricing, returns and fraud decisions through agents.

See our E-Commerce & Retail AI work

Who Builds and Supervises Your Agents

A founder leads every engagement. Here is who designs your agents, the data they act on and the guardrails around them.

Alexander Soldatov

Product Lead

Ten years leading products at Yandex, AliExpress and Tinkoff, with operations he scaled from zero to 23 specialists. He picks the workflow an agent should own first and defines where a human must stay in the loop.

Vladislav Volovik

Data & Analytics Lead

Five years building SAP Analytics BI at Allianz Technology and e-commerce analytics at Sephora (LVMH Group). He designs the data layer and evaluation metrics that decide when an agent is accurate enough to act alone.

Sergey Rodin

Managing Partner

Founder of Lava Media in San Diego, with 900+ campaigns for brands including Reebok, 3M and Vivo. He owns your engagement end to end: scope, commercials, timelines and the approval rules agreed with your team.

The founding team has run AI assistants and support automation serving millions of customers; our engineers average 5–7 years of senior experience.

What Makes an Agent Safe to Trust

Our team answers the questions operations leaders ask before letting software act on their behalf: what to delegate, how to measure accuracy and what an agent costs to run.

Ready to Put Your First AI Agent Into Production?

Bring one workflow your team repeats every day. A solutions architect, not a salesperson, will tell you whether an agent can own it, what it would cost and how it would be supervised.