Generative AI
Generative AI development for drafting, search, and assisted work
Generative AI is useful when the job is language: drafting a reply, summarising a file, or turning a question into a search over material you trust. We build that into a product with sources, limits, and a record of what was generated.
- Assisted drafting
- Summaries
- Controlled generation
- Human review
Where generation belongs
Customer replies, internal summaries, listing descriptions, and first drafts of routine documents are common fits. Decisions that move money or access should stay with a person, even if a model prepares the brief. We design the handoff explicitly.
Grounding and evaluation
A model that only knows the public internet will invent your policies. We connect generation to approved sources, refuse questions outside that set when that is the right behaviour, and keep a small evaluation set of real questions so changes to the prompt or model are not judged by a single demo.
Drafting with your rules
Generated inside the product
- A draft from your own content
- A template a person can edit
- A record of what was generated
Not this release
- Open-ended chat with the public web
- Publishing without review
- A new brand voice invented by the model
What changes generative work
The output
An email, a listing, and a summary have different review rules.
The source
Generation from your catalogue is useful. Generation from nothing is a liability.
Who sends it
The person accountable for the customer still sends or approves the text.
What a drafting brief needs
- 01
The output
An email, a listing, or a summary.
- 02
Your content
The catalogue or templates it must use.
- 03
The reviewer
Who sends or approves the text.
- 04
The record
Whether the draft is stored, and where.
Marks generated text is safe to use
- 01
It has a use
The draft is a message, a summary, or a record someone asked for.
- 02
A person reviews
Nothing is sent to a customer or written to the system of record without a check.
- 03
The prompt is kept
The instruction that produced the draft can be found and changed.
- 04
Failure stays a draft
A bad generation is discarded. It does not send itself.
What we build
Assisted drafting
Replies and documents that start from your templates and the customer record, not from a blank prompt box.
Summaries
Long threads, reports, or policies reduced for a role, with a link back to the source.
Controlled generation
Style, language, and topics the system is allowed to touch, written as product rules.
Human review
A queue for anything the business is not willing to send automatically.
How an engagement runs
- 01
Pick one job
A single class of document or question, with examples of a good result.
- 02
Attach the sources
The files or records the draft is allowed to use.
- 03
Measure before you widen it
A reviewed sample, then a larger audience.
Questions we hear
Which model do you use?
The one that meets the quality, language, latency, and data-handling constraints of the job. We are not tied to a single vendor, and we do not send confidential text to a service your policy forbids.
Can this run in Arabic and English?
Yes, when we evaluate both. Fluency in a demo is not the same as correct policy language. Bilingual review is part of the test set.
Is generative AI the same as a chatbot?
A chatbot is one interface. Generation is also used inside CRM screens, document tools, and back-office queues. See the chatbot and assistant pages for those shapes.