Custom AI Agent Development
An AI agent that does real work in your systems, under your rules — tool catalogue, approval modes and an eval set, in a 10–24 week planning band.
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Custom AI agent development means building an AI agent around your business rules that can carry a job from start to finish: it plans steps, calls the tools in your systems (APIs, databases, email, payments) and keeps its state along the way. GG Tech Teknoloji's Custom AI Agent Development service writes down which tools the agent may use, what it must ask a person about and how its quality will be measured before any code is written; the agent does not go live until it passes its eval set. Our planning band is 10–24 weeks.
| Typical team | 1 PM (part-time) + 2 AI engineers + 1 backend developer |
|---|---|
| Calendar band | 10–24 weeks |
| Phase split | 20% domain modeling & tool catalog · 45% development · 25% evals & hardening · 10% rollout & handover |
What grows the budget
- Number of tools
- Memory architecture
- Autonomy level
- Compliance requirements
Signs of underbudgeting
- No eval regimen
- A "we'll fix it with prompts" architecture
These are GG Tech Teknoloji planning bands, not a quote; starting prices are on each service page. Every project is different, so the bands are deliberately wide; they assume a senior, focused team and typical scope, and your project is estimated individually.
Who is it for?
- Companies that want to hand over repetitive work that still needs judgement — the kind an employee carries between several systems every day.
- Businesses that want customer-facing replies automated in their brand voice, but under an approval check.
- SaaS teams that want to add an assistant that does things on the user's behalf.
- Teams that found off-the-shelf chatbot tools cannot connect to their systems or carry their rules.
When is it the wrong choice?
- All you need is question-and-answer and the agent will never act in any system: a RAG assistant or a well-built chatbot is enough.
- The process follows the same steps every time and needs no judgement: classic workflow automation is cheaper and more predictable.
- Nobody will notice and correct a wrong action by the agent: define the approval mode and ownership first; autonomy comes after.
How do we work?
- 1
Task and decision map
The job the agent takes over is written step by step: what information it starts from, which decisions it makes, where it stops and asks a person. The work an employee does today is the best draft of what the agent will do.
- 2
Tool catalogue
Every system the agent touches is defined as a tool: what it does, which parameters it takes, which permission it runs under. Read tools are separated from write tools, and irreversible actions are flagged.
- 3
Autonomy level and approval modes
You decide how freely the agent works: it acts on its own, drafts and waits for approval, or only notifies. The mode can differ per type of work and change at any time.
- 4
Quality-check layer
Every output that leaves the agent passes a separate check before it is published: is it on topic, is it made up, does it promise something it should not. An output that fails is not published and goes to a person.
- 5
Eval set and hardening
A test set is built from real examples, and the agent is measured against it after every change. Success means results on the set, not an impression from a demo.
- 6
Go-live and handover
The agent opens first on a narrow scope under a strict approval mode, with token spend, loop counts and tool calls monitored. Your team is trained to manage the agent's tools and prompts.
What do we deliver?
Custom AI Agent Development
What sets the timeline and cost?
In our estimation model, custom AI agent development sits in a 10–24 week calendar band. Four things move it most: the number of tools the agent uses, the memory architecture (what it remembers and for how long), the level of autonomy and compliance requirements. An architecture with no eval regimen, built on "we'll fix it with prompts", is the earliest sign that the budget will not hold. A fixed-scope 4–6 week pilot starts at $25,000 (excl. VAT); the full project is budgeted in a written proposal once the task and tool map exists. The Cost Drivers page explains how to read the bands.
See the cost driversProof from production
3
approval modes — automatic, hybrid and manual — chosen per business and per star rating
7
onboarding steps run as a conversation instead of a settings form
3
attempts, after which a reply that fails the quality check is not published and goes to the owner
All three figures come from Beyond Review, which we built for Beyond Creator, and were read from its source code (September 2026).
Read the case study: Beyond CreatorFrequently asked questions
What is the difference between an AI agent and a chatbot?
How long does it take to develop an AI agent?
What happens if the agent does something wrong?
How do you measure an agent's quality?
Which model do you use — will we be locked into one provider?
How are agents governed for data protection and AI oversight?
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Agentic Workflow Automation
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Work we delivered with this service
Related reading
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