Agentic AI integration
Agentic AI integration without fine-tuning.
CodeFlow, an independent software consultancy in Athens, Greece, builds LLM, OCR and embedding features into the production systems of software companies and in-house development teams, through existing model APIs and agents.
“Without fine-tuning” means we use available models and do not train or fine-tune them. We combine model APIs with retrieval over your data, OCR, embeddings and agents instead. That keeps complexity and time to delivery down, and focuses the work on functionality that pays off directly.
Who it is for
Small and medium development teams.
We work with software companies, and with in-house teams inside non-software companies that build and run their own systems. Agentic AI integration suits teams that want LLM, OCR or retrieval features in their systems and prefer to build on available models.
Scope
What is included, and what is not.
The scope is defined up front, so you know what the work covers and what it does not.
Included
- Use-case assessment: what is feasible, and what it will cost to run
- Agent architecture on top of existing model APIs
- Retrieval (RAG) pipelines: embeddings, search index, access control
- OCR and structured extraction from documents
- Evaluation sets, output validation and monitoring
- Integration with your services, data and authentication
Not included
- Training or fine-tuning models
- Large-scale data labelling
- Machine learning research
- Guarantees of model accuracy: outputs are probabilistic, so we measure and constrain them
- Legal or regulatory assessment, e.g. under the EU AI Act
How it works
From use case to a measured system.
Assess the use case
What is feasible with existing models, and what it will cost to run.
Build on existing models
Agent architecture, retrieval, OCR and extraction, integrated with your services, data and authentication.
Evaluate and monitor
Evaluation sets, output validation and monitoring, because outputs are probabilistic.
At a glance
The service in brief.
Existing models, a defined scope, and output that is measured and constrained.
| Service | Agentic AI integration |
|---|---|
| Approach | Existing model APIs. No training or fine-tuning. |
| Building blocks | Agents, retrieval (RAG) with embeddings and a search index, OCR and structured extraction |
| Engagement | B2B contract, scoped work, no long-term commitment |
| Based in | Athens, Greece |
| First reply | Within one business day |
Questions
Agentic AI integration questions.
Do you fine-tune models?
No. We use available models through their APIs and do not train or fine-tune them. That keeps complexity and time to delivery down, and focuses the work on functionality that pays off directly.
Can you guarantee the accuracy of a model’s output?
No. Model outputs are probabilistic, so we do not guarantee accuracy. We measure output quality with evaluation sets, constrain it with output validation, and monitor it once the system is running.
How do you decide whether a use case is feasible?
Every engagement can start with a use-case assessment: what is feasible, and what it will cost to run.
Can the system work with our own documents and data?
Yes. Retrieval (RAG) pipelines cover embeddings, the search index and access control, and OCR with structured extraction handles data in documents. We integrate with your services, data and authentication.
Do you do machine learning research or data labelling?
No. Machine learning research and large-scale data labelling are outside the scope of this service.
Do you assess legal or regulatory requirements, such as the EU AI Act?
No. Legal and regulatory assessment is not part of this service.
How do we start?
Send us a short description of the use case and the systems involved through the contact form. We reply within one business day.
Considering an agentic AI feature?
Describe the use case and the systems it has to work with. We reply within one business day.