Custom AI Agent Development Company

n8n, Make.com and Zapier automation with AI steps and a human approval check — fixed price, documented on handover.

Custom AI Agent Development, From Single Agents to Multi-Agent Systems

Eicra is an AI agent development company in Dhaka that builds software agents to plan a task, call your tools and act inside your systems. Our agents work in your customer relationship management (CRM), enterprise resource planning (ERP) or helpdesk software. A person approves anything that matters, and every agent is tested on 20–50 of your real cases before launch.

An in-house team that builds, tests and operates production AI agents — not prototypes.

One exit at each step. No long-term commitment at any of them.

Our engineers map one task with the people who do it today. Every step is documented, every exception is counted, and every automation option is costed in your own numbers.

You get a written verdict — single agent, multi-agent, workflow or nothing. If nothing in it justifies a build, you stop here.

Book a Diagnostic

Time4–5 weeks to a working agent, tested on 20–50 of your real cases

TeamYour time zone Our engineers, one weekly call, written change log

RiskStop at any step Each step ends with a written result; no production fee if the pilot fails

OwnershipYou own it Code, prompts, test set and runbook exported to you at handover

What is included in an offshore AI agent development project?

Each AI agent project includes six deliverables: a written agent design, a working agent in your own accounts, a test set with an accuracy gate, guardrails with a human approval step, monitoring with a kill switch, and a runbook with admin handover. You receive a working agent and the controls that keep it safe, not a demo.

Agent design and tool-calling plan

A written design: the task, the tools the agent may call, the data it may read, the decisions it may take alone and the ones it must hand to a person.

Built in your own cloud and model accounts

One agent for one job, built with supported APIs inside your hosting and your model account, so nothing depends on a platform we control.

Test set and accuracy gate

Twenty to fifty real cases become the test set; the agent must pass an agreed accuracy gate before every release, with regression tests when prompts or models change.

Guardrails and human approval

Least-privilege access, approval gates for money, records and customer messages, and a log of every tool call and decision.

Monitoring, alerts and kill switch

Alerts on failures and cost spikes, a per-run spend cap, and a switch that stops the agent within minutes.

Runbook, training and handover

Code, prompts, configuration, test set and runbook exported to you; team training; admin access transferred at handover.

Not included: AI model usage fees (paid by you to the provider) · tool and hosting subscriptions · work beyond the agreed scope, priced first as a change request.

AI agents for customer support

Reads tickets, drafts replies, routes exceptions to a person.

AI agents for invoice and PO matching

Matches each invoice to its purchase order (PO), flags exceptions, waits for approval.

AI sales agents for lead qualification

Qualifies leads, enriches them, books the follow-up.

AI agents for operations and work orders

Assigns work orders, updates your system, escalates when unsure.

How does AI agent development work, from scoping to launch?

AI agent development runs in five steps: a free 30-minute scoping call, a five-day diagnostic, a three-to-four-week pilot of one agent on real cases, a four-to-eight-week production build with guardrails and rollback, and optional Managed AI Ops after launch. Prefer to hire AI developers monthly instead? See our dedicated team option. Each step ends with a written result.

01 30 min · free

Scope A call about the task you have in mind. If you already know the process, you leave with a pilot quote.
02 5 days

Diagnose One process, one 45-minute call, and a written verdict: single agent, multi-agent, workflow or nothing.
03 3–4 weeks

Pilot One agent built in your accounts and judged on 20–50 of your real cases, with a go/no-go report.
04 4–8 weeks

Production The tested agent goes live with approval gates, a kill switch, a runbook and 30 days of free fixes.
05 Monthly · optional

Managed AI Ops Accuracy checks, model and prompt updates, and a monthly report. Cancel any month; the agent stays yours.

First AI agent timeline

A first agent usually goes live in seven to thirteen weeks: a free scoping call or a five-day diagnostic, a three-to-four-week pilot judged on 20–50 of your real cases, then a four-to-eight-week production build with approval gates and a kill switch. Multi-agent systems take longer and are scoped after the pilot. Prices are on our pricing page.

Team AI engineers and a quality lead

Tools CRM, ERP, helpdesk via supported APIs

Communication Weekly call, shared channel, change log

AI models OpenAI, Claude or Gemini, on your own key

Guardrails Approval gates, spend cap, kill switch

Hosting Your own cloud and model accounts

What is AI orchestration for multi-agent systems?

AI orchestration is the coordination of several models, agents and tools in one workflow: a planner that splits the task, specialist agents that do each part, and a controller that checks results, retries failures and hands exceptions to a person. We build it only when one agent measurably cannot do the job.

Does your task need an agent? Answer five questions.

1. Same steps every time?

2. Systems it touches

3. Reads free text or documents?

4. If one case goes wrong

5. Cases per month

A single agent, with an approval gate

Free text or judgement calls, but one job: a pilot in 3–4 weeks on 20–50 of your real cases.

Book a Diagnostic A first estimate; the diagnostic confirms it.

Agent run · invoice #4821

Read invoice PDFVendor, amount, PO extracted

Match to PO and bankAmount differs by 2.1%

Decision: needs reviewConfidence 62% · below the 90% gate

Approval gateA person approved · 45 s

Posted to ERPLogged · 12 s · USD 0.03 model cost

Illustrative run

Yellow = a person decides

Every step logged

Kill switch on every agent

How the verdict is decided: same steps, one or two systems and no free text → a workflow, not an agent · free text or judgement calls in one job → a single agent with an approval gate · three or more systems and several distinct tasks → a multi-agent system, scoped after a single-agent pilot · under 100 cases a month or a process still changing → not yet.

Workflow, single agent or multi-agent system: which does your task need?

Your task	Our verdict	What happens next
Same steps, one or two systems, no free text	A workflow, not an agent	A rules-based workflow, cheaper and safer than an agent
Free text or judgement calls in one job	A single agent with an approval gate	A pilot in 3–4 weeks on 20–50 of your real cases
Three or more systems and several distinct tasks	A multi-agent system	Scoped after a single-agent pilot, never before
Under 100 cases a month or a process still changing	Not yet	A free 30-minute scoping call; revisit when volume grows

Why choose Eicra as your AI agent development company?

Tested before launch. Owned by you after it.

An AI agent development company designs, tests and runs software agents for other businesses. Our AI agent development services work proof-first: every agent has a test set, a human-in-the-loop approval step and a kill switch before it touches production. It is designed to support the human oversight that Article 14 of the EU AI Act requires for high-risk AI systems.

Which companies are developing AI agents? Large AI firms ship general-purpose agents, such as OpenAI’s ChatGPT agent, Anthropic’s Claude, Google’s Gemini and Microsoft Copilot. Custom agents that run one task inside your own systems are built by development companies like ours. The best AI agent development company for your task pilots on your real cases, gates risky actions and hands you the code.

AI agents built without a tested process

!!!!!

A demo that works on 5 examples, then fails on real cases
An agent that acts before anyone approves
Hourly quotes that grow as the scope drifts
Code and prompts on a platform you cannot leave

AI agents built with Eicra’s tested process

Pilot report · Invoice-matching agent

Cases tested40Accuracy gate95%Approval gateOnVerdictGo to production

✓ Passed the agreed gate

Illustrative example

Judged on 20–50 of your real cases before production
Approval gates for money, records and customers; kill switch
Fixed prices at every step; production quoted in writing
Code, prompts and test set exported to you; subscriptions in your name

What proof does Eicra give before you pay for an AI agent?

The proof you get before you pay is evidence, not promises. You get sourced market data, a pilot judged on your own cases and a free 30-minute review of one task before you pay anything. Client case studies with numbers are added here as clients give permission to name them.

40%+ Agentic AI projects expected to be cancelled, citing escalating costs, unclear business value or inadequate risk controls. Source: Gartner, June 2025

USD 576B Gartner’s latest forecast for worldwide AI services spending, up about a third on the year before (USD 434 billion). Source: Gartner, September 2026

25% Share of AI initiatives that had delivered their expected return on investment (ROI), according to a survey of 2,000 chief executives. Source: IBM CEO Study, May 2025

Case studies: client results with numbers are added here as clients give permission to name them. Ask on the scoping call for references in your industry.

Free 30-minute task review Send one task you think an agent could do. You get a written note on whether it needs an agent, a workflow or neither, and what it would cost, whether or not you hire us.

Send one task

Is it safe to outsource AI agent development?

Outsourcing AI agent development is safe when the agent’s permissions are agreed in writing before it acts. The risks are an agent reaching data it should not, taking an action nobody approved, or running up a model bill. We close all three before launch.

IBM’s breach report found 97% of organisations breached through AI lacked proper access controls. The Open Worldwide Application Security Project (OWASP) names this risk in its Top 10 for Large Language Model Applications. Its definition, for any large language model (LLM), reads: “Excessive Agency is the vulnerability that enables damaging actions to be performed in response to unexpected, ambiguous or manipulated outputs from an LLM, regardless of what is causing the LLM to malfunction.” The National Institute of Standards and Technology (NIST) sorts AI risk work into four functions in its AI Risk Management Framework: govern, map, measure and manage. Intellectual property (IP) in the delivered work is assigned as the contract sets out.

Contracts and data transfer

Which agreements are signed before AI agent development starts?

Non-disclosure agreement (NDA) — mutual, signed before we touch any system.

Data processing agreement (DPA) — the processor terms required by Article 28(3) of the General Data Protection Regulation (GDPR) and the UK GDPR, for any personal information.

Data transfers — EU standard contractual clauses, the UK International Data Transfer Agreement (IDTA) or Addendum, or Singapore Personal Data Protection Act (PDPA) transfer clauses, signed before personal data moves.

Model provider terms — application programming interface (API) tiers whose terms exclude training on your data, where offered, recorded in the runbook.

Certifications — listed only when held; none are claimed on this page.

Controls, IP and service levels

What controls, IP and rework terms apply to an outsourced AI agent?

Access Least-privilege scopes for the agent, credentials held in your accounts, our logins removed at handover.

Approval gates Money, records and customer communication wait for a person; every tool call and decision is logged.

Kill switch The agent can be stopped in minutes, and no run can exceed an agreed model spend.

Ownership Delivered work as set out in the contract; subscriptions stay in your name.

Service level agreement (SLA) and rework Response times in the signed terms; rework free when a delivered agent fails the agreed test cases; changes priced first as a change request.

Request our NDA, DPA and data transfer templates

AI agent development FAQs: cost, timing and frameworks

How much does AI agent development cost?

AI agent development with us starts from USD 199 for the diagnostic and USD 800 for a fixed-price pilot of one agent. Production starts from USD 1,500 per agent, and multi-agent systems from USD 3,000. A free scoping call or a five-day diagnostic comes first. Prices are in US dollars.

How long does it take to build an AI agent?

From first call to a working pilot is usually four to five weeks: a free call or five-day diagnostic, then three to four weeks to build and test one agent on 20 to 50 real cases. A live production agent takes seven to thirteen weeks end to end; multi-agent systems take longer, quoted after the pilot.

What is the difference between an AI agent and agentic AI?

An AI agent uses a model to decide the steps and call tools; agentic AI, or a multi-agent system, is several such agents coordinated by a controller. Most business tasks need one well-tested agent, not a fleet. In the diagnostic we test the single-agent version first and add orchestration only if it fails.

Which AI agent frameworks and models does Eicra use?

We build with open agent frameworks such as LangGraph, or directly on supported APIs, chosen per project on tool count, memory needs and your hosting rules. Models from OpenAI, Anthropic and Google are compared on your own test cases, as in our AI integrations work. The code, prompts and configuration are exported to you at handover.

Can an offshore team build a reliable AI agent?

Yes, if the process is built for it. We test every agent against a set of 20 to 50 real cases before it touches production, log every tool call, and put a human approval step in front of any action that changes money, records or customer communication. You judge the pilot on measured results.

How do you stop an agent from doing damage?

Three controls: least-privilege access, so the agent can only reach the tools and records the task needs; approval gates, so money, records and customer messages wait for a person; and a kill switch plus alerts, so a misbehaving agent is stopped within minutes. All three are set up in the pilot, not after launch.

Who owns the agent and its code?

You do. The agent runs in your accounts and your hosting, and at handover you receive the code, prompts, configuration, test set and runbook. Ownership of the delivered work is set out in the contract, model and tool subscriptions stay in your name, and nothing depends on a platform we control.

Can we hire AI developers monthly instead of a fixed-price project?

Yes. If you have ongoing agent work, you can hire AI developers from our team on a monthly contract with a three-month minimum, a quality assurance (QA) lead and a named replacement if someone leaves. Most clients start with one fixed-price pilot, then move to a monthly team once the workload is clear. If the agent has to be built inside your own repository and pipeline instead of ours, a forward deployed engineer embeds with your team for that work.

Start your AI agent with a free 30-minute scoping call or the five-day diagnostic. You leave with a written verdict — single agent, multi-agent, workflow or nothing — whether or not you hire us.