AI Agent Development · Fixed-Scope Pilots

AI agents that do the work — not just answer questions about it

Our agents read documents, update systems, and finish real work — in finance, support, HR, sales, logistics, and more. A human approves anything sensitive. One of our systems runs a client's entire finance department right now. Yours starts as a $5k–$25k pilot on a single workflow, live in 2–4 weeks.

Scope your pilot → See exact pricing
Finance OSagentic system live at Krish Ventures
$5k–$25kfixed scope, agreed before we start
2–4 weeksfirst workflow in production
Local LLMsruns offline — no GPT or Claude needed

The full agentic scope

What an agent can actually do — in any department, any industry

An agent is not a chatbot. It's software that does real work inside your systems, following your rules. We've built and shipped every capability below — and we can show you each one working.

Works in your systemsReads and updates your CRM, ERP, sheets, and databases. It can only do what you allow.
Handles documentsReads invoices, contracts, claims, and forms. Pulls out the data. Checks it against your rules. Acts on it.
Finishes multi-step jobsTakes a goal, works through the steps, handles surprises, and asks a human when unsure.
Talks to peopleAnswers customers and staff from your real data. Cites its source. Says "I don't know" instead of guessing.
Works as a teamSeveral agents hand work to each other. That's how we automated an entire finance department.
Runs without internetOn your own machines, on local models. No OpenAI. No Anthropic. Your data stays in the building.
Runs itselfOn a schedule or on a trigger — nightly reconciliation, instant ticket replies, weekly reports.
Answers to youEvery action is logged. Sensitive steps wait for a human click. You can override anything, anytime.

Where agents earn their keep

Find the workflow that eats your team's week

Pick the row that sounds like your week. We start there, with one workflow, and prove it works.

Finance

Invoices, reconciliation, reporting

Reads invoices. Matches them to orders and bank entries. Flags what's off. Drafts the report. A human approves every payment.

Live today: Finance OS runs a real finance department.
HR & People

Hiring, onboarding, payroll

Screens applications. Prepares onboarding. Keeps payroll data correct across systems.

We built a full payroll platform — live in 1 week.
Customer support

Real answers, not scripts

Answers any question from your actual docs and product data. Escalates what it can't handle.

Built on our proven RAG stack.
Sales & marketing

Research and first drafts

Finds and researches leads. Scores them. Drafts the outreach. Your team hits send.

Humans stay on the send button.
Operations

Copy-paste work, gone

Moves data between systems. Chases status updates. Fills forms. Routes requests.

The most common first pilot we build.
Documents & legal

Read, check, decide

Reads contracts and claims. Checks them against your rules. Drafts the decision with reasons attached.

Every step logged and auditable.
Healthcare & pharma

AI where data can't leave

Your team asks questions in plain language. The AI answers from internal documents — all on your own machines.

Shipped for Aru Pharma. Zero outside API calls.
E-commerce & retail

Catalog, orders, stock

Enriches product data. Resolves order issues. Watches inventory. Drafts review replies.

Built to plug into your existing store.
Real estate

Listings, leads, paperwork

Syncs listings. Qualifies inquiries. Prepares documents. For brokers, portals, and proptech products.

We also build proptech — including tokenized ownership.
Travel & booking

Search, compare, book

Searches flights, hotels, and trains across providers. Compares real prices. Books with your approval.

Plain-language search over live provider data.
Logistics

Delays caught early

Tracks shipments. Spots delays. Proposes fixes. Drafts the carrier email — before the customer notices.

Agents shine exactly where delays cost money.
Your industry

The one we didn't list

If the work has rules, systems, and repetition — an agent can run it. Tell us yours.

30 minutes. A straight answer. No pitch.

The pilot, concretely

What you get for $5k–$25k

Not a slide deck. A working agent, in production, on one workflow you chose — with everything your team needs to trust it and run it.

  • A working agent running one agreed workflow in production
  • Integrations with the systems that workflow touches
  • Human-approval gates on every sensitive action
  • Guardrails: step limits, tool contracts, loop detection
  • Full audit log of every action the agent takes
  • A dashboard your team uses to watch and override it
  • Documentation and a working session with your team
  • A written expansion plan: what to automate next, and what it costs
Week 1We map the workflow with the person who actually does it — every step, every exception, every system it touches.
Weeks 2–3Build and integrate. The agent runs in shadow mode against real cases; we tune until its decisions match your team's.
Week 4Production, with human approvals on. You watch the audit log, we tighten guardrails, your team takes the keys.

Proof, not promises

Finance OS: the agent system running a real finance department

Krish Ventures came to us with a finance back office drowning in repetitive work — accounts payable and receivable, bank reconciliation, monthly reporting. The volume grew; hiring more people to copy numbers between systems felt like the wrong decade's answer.

We built Finance OS: a system of agents that runs those operations end-to-end. Agents read documents, match transactions, prepare entries, and draft reports. Nothing sensitive happens without a human click — approvals are designed in, not bolted on, and every action lands in an audit trail their accountants can read.

We didn't automate the department in one leap — that's how these projects fail. One workflow first. Prove accuracy. Then the next. That's the same playbook your pilot starts.

Automate one workflow in weeks. Expand only when the numbers prove themselves.
End-to-endAP/AR, reconciliation & reporting run by agents
Human-approvedevery sensitive step gated by a person
Fully auditedevery agent action logged and traceable
In productionrunning a real company's finance ops today

Know the number before the call

Single-workflow pilots run $5k–$10k. Multi-step operations agents $10k–$18k. Multi-agent systems $18k–$25k. We published the whole breakdown — costs, timelines, and what moves the price — because guessing games waste your time and ours.

Read the pricing guide →

How we build agents

A delivery process built for trust, not demos

Agents fail in production when they're built like chatbots. Ours are built like systems — with the boring engineering that makes them safe.

Workflow mapping

We sit with the person who does the job. Steps, exceptions, systems, the unwritten rules — all of it, before any code.

Agent design

State machines (LangGraph), strict tool contracts, and step limits — the agent can only do what we've explicitly allowed.

Shadow mode

The agent runs against real cases without touching anything. We compare its decisions to your team's until they match.

Gated production

Live, with human approval on sensitive actions and a full audit log from the first minute.

Expand on evidence

When the numbers prove out, we add the next workflow. That's how one pilot became a whole finance department.

How we work & why it matters

We combine process, technology, and expertise so your product gets built right—from idea to launch.

We use proven stacks and clear delivery so you get results you can measure.

Technologies we use

We build with the stacks and tools your product needs.

🔗LangGraph / LangChain
🚢CrewAI / Autogen
🧠OpenAI / Anthropic
🧬LlamaIndex RAG
🛡️Guardrails / NeMo
☁️Modal / AWS Lambda

Common questions

What is AI agent development? →

AI agent development at Essen Software is building autonomous agents that use LLMs, tools, and state machines (e.g. LangGraph) to perform tasks—with human-in-the-loop controls and strict safety guardrails.

How do you prevent AI agent loops and errors? +

We use state machines (LangGraph) with step limits and semantic error detection to stop repetitive or unsafe actions. Sensitive steps go through approval gates so a human stays in control.

Can AI agents access our internal systems safely? +

Yes, via tool wrappers that enforce SQL templates, read-only access where needed, and audit logs. We never expose raw DB access to the agent.

Can AI agents automate an entire department like finance or HR? +

Yes — in stages. We built Finance OS for Krish Ventures: an agentic system running their finance department's operations end-to-end (AP/AR, reconciliation, reporting) with human approval on sensitive steps. The playbook: automate one workflow first (2–4 weeks), prove accuracy, then expand workflow by workflow until the department runs on agents with human oversight.

Can agents run on local LLMs without internet — no GPT or Claude? +

Yes. We build agents on local models (Llama, Mistral, Qwen) running on your own hardware — zero external API calls, fully offline capable. This fits regulated and data-sensitive teams. The trade-off: local models need tighter guardrails and slightly narrower scopes than frontier APIs, and we design for that with state machines and strict tool contracts.

Why choose Essen for AI agents

⚡
Rapid POC
Agentic MVP in 4 weeks
🛡️
Policy First
Zero-trust agent permissions
📊
Observable
Full trace logs for every plan
🌌
Scalable
From 1 agent to 1,000 workers
Hire an AI Colleague →

Tell us the workflow that eats your team's week

Thirty minutes. You describe the workflow, we tell you honestly whether an agent fits, what it would cost, and how fast it can be live. If an agent is the wrong tool, we'll say so.

Scope your pilot