AI development

AI features that answer from your data, with sources, and hold up in production: assistants, smart search, summarisation and document intelligence for the software you already run.

Get a fixed quote

Included

What our AI development covers

Ask-your-documents systems

Assistants that answer staff questions from your SOPs, contracts and manuals, with citations to the source.

Smart search

Search that understands meaning, not just keywords, across your records, tickets and files.

Document intelligence

Invoices, forms and reports read automatically into structured data, with human review where stakes are high.

Summarisation pipelines

Long reports, threads and calls condensed into summaries your team actually reads.

AI feature integration

AI capabilities added into your existing Laravel, React or Flutter product as features, not a rebuild.

AI Readiness Audit

A fixed-fee, 2 to 3 week assessment mapping where AI pays back in your operations, with cost per use case.

Stack

Tools we use for this work

OpenAI API RAG pipelines LangChain Vector search Embeddings Laravel Python Human-in-the-loop

Why us

Why teams choose Codespark

Anchored, not hallucinating

Retrieval pipelines tie every answer to your documents, with citations. Accuracy is engineering, not luck.

Fixed-price first steps

AI engagements start with a fixed number, so you know the cost before you commit.

Honest about limits

If AI is the wrong tool for your problem, we tell you before you spend, not after.

Approach

Your data stays yours

Client data is never used to train public models. We sign NDAs before seeing anything, apply role-based access inside every AI system, and design EU-grade data handling by default, including self-hosted model options where residency demands it.

Questions

Common questions

How much does an AI project cost?

Entry points are deliberately small: the AI Readiness Audit is fixed-fee, and first production features typically run $5,000 to $20,000. You always know the number before committing.

What happens when the AI gives a wrong answer?

Our systems answer from your own documents with source citations, and human review sits wherever stakes are high. Where accuracy cannot be guaranteed, the design says so instead of pretending.

Is our data used to train AI models?

No. Your data is never used to train public models. Access is role-based, retention is minimal, and self-hosted options exist for strict residency requirements.

Do we need our own data science team?

No. We design, build and operate the full pipeline, and hand over documentation your regular IT team can own.