Custom Writing Prompts
AI prompt engineering services turn the way your content team asks an AI model to write into a system: system prompts that carry your brand voice, a reusable prompt library for each content type, guardrails that catch errors and invented facts, and tests that prove the output before it is published. As a Dhaka-based company, we build that system inside your own AI accounts, for international companies, at a fixed price per step, with prompt engineers and an editor who score every template on your own past content before your writers see it.
One exit at each step. No long-term commitment at any of them. We start with the one content workflow where AI output is rewritten most today: blog drafts, product copy, email, social. Its writers, tools, style rules and last 20 pieces are reviewed, the smallest prompt system that removes the rewriting is defined, and it is costed in your own numbers.
You get a written verdict — a prompt system for one workflow, a library for the whole team, an automated workflow, an AI agent, or nothing yet. If nothing justifies a build, you stop here.
30 minutes 01 Scope · free call
5 days 02 Diagnose · $99, credited to the pilot
1–2 weeks 03 Pilot · $399 fixed
3–4 weeks 04 Production · $800 per further workflow
Monthly 05 Managed Ops · $499 a month, up to five workflows
What is included in AI prompt engineering services?
AI prompt engineering services design, test and maintain the instructions a large language model (LLM) follows to write for your brand: the system prompt that holds voice and policy, a template per content type, the worked examples the model imitates, guardrails that check facts and tone, a test set that scores each template, and the documentation your team keeps.
Brand-voice system prompts
The standing instruction every template inherits: reader, tone, banned claims, formatting, sources allowed, and what to do when a fact is missing.
Reusable prompt library
One template per content type — blog, landing page, email, social, product copy — with inputs, rules and examples written in, versioned and shared.
Few-shot example sets
Your best past pieces, cleaned and annotated, so the model imitates what already worked for your readers instead of an average of the internet.
Guardrails and quality checks
A second pass that checks names, numbers, quotes and claims against the source, flags tone breaks, and marks anything unverifiable for the editor.
Prompt testing and scoring
Every template run on 20 briefs, scored by your editors on a fixed rubric, and iterated until the score holds; the test set stays with you.
Handover and upkeep
A usage guide, a one-hour training session for writers and editors, and optional monthly upkeep as models and tools change, with a named engineer.
Not included: AI model and writing-tool subscriptions, which stay in your own accounts · hourly advice · pipelines that move content through several tools without a person (workflow automation) · software that publishes, replies or decides on its own (an AI agent) · new content types, priced first as a change request.
What does a custom AI prompt library for business include?
A custom AI prompt library for business is one place where every prompt your team uses lives, versioned and tested: a template per content type, the brand rules and examples baked in, and the test set that proved it. It is what makes ten writers produce one voice, and it is kept current under Managed Ops as models change.
Content-type templates
One template each for blog, landing page, email, social and product copy, with the brand rules already inside.
Inputs and variables
The brief fields a writer fills — audience, offer, keyword, length — so the prompt never depends on memory.
Versions and change log
Every edit numbered and dated, with the test score before and after, so a bad change can be rolled back.
Usage guide
A short guide per template: when to use it, what to check, and what the editor signs off before publishing.
How is a production prompt built and scored in AI prompt engineering services?
AI prompt engineering services build each production prompt in layers and score every version on the same 20 briefs before handover. Click a layer to see what it holds and what it changed in a sample blog and landing-page pilot, where version 3 lifted the editor score from 6.1 to 8.4 of 10.
Prompt system · blog draft template
What this layer holds · result in the pilot
System prompt · brand voice
The standing instruction every template inherits.
ReaderToneBanned claimsFormattingSources allowedWhat to do when a fact is missing
Inherited by 6 templates
6.1of 10
Version 1 in the pilotSystem prompt and 6 templates drafted, scored on 20 briefs
Template inputs
The brief fields a writer fills, so the prompt never depends on memory.
Brief · filled by the writer
{audience}{offer}{keyword}{length}One template per content type
BlogLanding pageEmailSocialProduct copy
4
Content types in the pilot1 workflow, a style guide and 20 samples received
Few-shot examples
Your best past pieces, cleaned and annotated, so the model imitates what already worked.
Without examplesAn average of the internet
With examplesWhat already worked for your readers
Change logEvery edit numbered and dated, with the test score before and after
Editor score, of 10Version 3 added examples and guardrails
Guardrails
A second pass before the editor, on every output.
- Names, numbers, quotes, claimschecked against the source
- Tone breaksflagged
- Anything unverifiablemarked for the editor
0
Invented facts in Version 3Scored on the same 20 briefs
Editor sign-off · a person signs
Every template run on 20 briefs and scored by your editors on a fixed rubric.
3 editors approved 18 of 20 outputs2 templates reworked
Handed overLibrary, tests and guide in your workspaceTraining done30 days of fixes
Click a layer, or a number below, to switch the result
When a model or tool changes, Managed Ops re-tests every template on the same briefs and updates the guardrails.
Illustrative example. Click a layer to switch the result; yellow marks the step where a person signs, and every item can be traced to a template version, a test run and an editor’s score.
How do AI prompt engineering services work, from scope to Managed Ops?
AI prompt engineering services run in five steps: a free scoping call, a five-day diagnostic that reviews one workflow and quotes the pilot, a one-to-two-week pilot that builds, tests and hands over its prompt system, production that adds the other workflows one at a time, then Managed Ops. Every step ends with a written result you can stop on.
01 30 min · free
Scope A call about the content workflow where AI drafts are rewritten most, the tools and the style rules in use. If those are known, you leave with a diagnostic quote.
02 5 days · credited
Diagnose Twenty past pieces, the style guide and the current prompts reviewed; the failure patterns named; the smallest useful prompt system defined; the pilot priced in writing.
03 1–2 weeks · fixed price
Pilot One workflow’s prompt system built: system prompt, templates, examples, guardrails, scored on 20 briefs by your editors, iterated, documented and handed over with training.
04 3–4 weeks each
Production The remaining content types and teams added one workflow at a time, each with its own test set and sign-off, plus a shared library, versioning and 30 days of fixes.
05 Monthly · optional
Managed Ops Re-tests when a model or tool changes, new templates, guardrail updates and a monthly review of scores, with a named engineer. Cancel any month; everything stays yours.
Who builds your prompt system, and with what?
A named team: a prompt engineer who writes and tests the templates, an editor who scores output against your rubric, and a project manager who runs the weekly review.
Content types Blog, landing page, email, social and product copy
Communication Weekly review call, shared channel, written change log
Delivery Your workspace, your model accounts, versioned templates
Quality assurance 20-sample test set, editor rubric, sign-off before handover
Training Usage guide and a one-hour session for writers and editors
Ownership Prompts, examples, tests and guide, all in your name
Do you need a prompt system, a shared library, an automated workflow, or an AI agent?
AI prompt engineering services take two forms: one or two writers rewriting AI drafts need a prompt system, and a team of ten with five content types needs a shared library. Content that moves through several tools without a person is a workflow automation; software that publishes, replies or decides on its own is an AI agent.
1. What does the team produce with AI?
2. How many people write with AI?
3. Are brand and style rules written down?
4. Must the content move through several tools automatically?
5. Should the AI publish, reply or decide on its own?
Which one do you need? Answer five questions.
A prompt system for one workflow, piloted first
One content type, one or two writers: a system prompt, templates, examples and guardrails, scored on 20 of your own briefs and handed over in one to two weeks.
A first estimate; the diagnostic confirms it.
How the verdict is decided
The AI acts on its own → an AI agent
Content moves through several tools end to end → a workflow automation
More than ten writers, or product, sales and support content → a shared library
Everything else → a prompt system for one workflow, piloted first
Why choose us as your AI prompt engineering company?
An AI prompt engineering company is judged on templates still in daily use a year later, not on a demo. We deliver custom AI prompt development as tested, versioned systems, priced in writing, in your AI accounts, with editor sign-off on real output and personal data in briefs handled under Article 28 of the General Data Protection Regulation (GDPR).
Without a staged process
!!!!!
- A prompt pack from a course, never tested on your content
- Every writer with a different prompt and a different voice
- Hourly advice that restarts each time a model changes
- Prompts in a consultant’s account you cannot open after the contract
With EICRA
Pilot report · Blog and landing pages
Templates6Test briefs20Editor score8.4Invented facts0VerdictHanded over
Illustrative example
- A named team, scores on 20 of your briefs before handover
- Fixed prices at every step; production quoted in writing after the pilot
- Prompts, tests and documentation in your workspace from day one
- Editor sign-off on real output before any template is called done
Is it safe to outsource AI prompt engineering?
Outsourcing AI prompt engineering to an offshore team is safe when accounts, data and ownership are settled in writing before the first draft. As a Bangladesh-based company, we work inside your AI accounts and workspace, assign prompts and tests to you, sign a data processing agreement before personal data flows, and hand back access at handover. Reviewed By Eicra.com team
Which prompt engineering agreements are signed, and when?
Confidentiality — a mutual non-disclosure agreement (NDA), signed before any brand document, sample or account credential is shared with anyone.
Data processing — an agreement (DPA) with processor terms under Article 28(3) of the GDPR and the equivalent national law, for any personal data that appears in a brief or a sample.
International data transfers — standard contractual clauses or the transfer instrument your jurisdiction requires, signed before personal data moves.
Access — your AI accounts and workspace, on your seats, with least-privilege roles; no copies of your content in ours.
Certifications — listed only when held; none are claimed on this page or in any proposal.
What prompt engineering controls, IP and rework terms apply?
Your accounts Templates, test sets and documentation are created in your workspace and your model accounts from day one; nothing is hosted on our side.
Ownership Prompts, examples, rubrics and tests are your intellectual property (IP), assigned to you in the contract; nothing is reused for another client.
Model settings Data-sharing and training options on your AI accounts are reviewed with you in the diagnostic and set before any sample is uploaded.
Personal data Briefs and samples are scrubbed of customer names and identifiers before they enter a prompt or a test set unless your DPA allows them.
Rework Free when a template fails its agreed score at sign-off; new content types are priced first as a change request.
What proof do you get before you pay for AI prompt engineering services?
Before you pay for AI prompt engineering services, you get evidence instead of promises: measured commitments, a pilot scored by your own editors on your own briefs before production is quoted, and a free 30-minute scoping call. Client case studies with numbers are added here as clients give permission to name them.
30 minutes
A free scoping call on the content workflow where AI drafts are rewritten most; if the tools and style rules are known, you leave with a quote.
20 briefs
Every template is run on 20 of your briefs and scored by your editors on a fixed rubric before it is handed over.
30 days
Of fixes after handover, with the library, tests and usage guide in your workspace and training for your writers and editors.
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.
What do buyers ask about AI prompt engineering services?
How much do AI prompt engineering services cost?
Our AI prompt engineering services are priced per outcome, not per hour, and each price is on the price cards at the top: a five-day diagnostic ending in a written verdict, credited to the pilot; a pilot that delivers one workflow’s prompt system, tested on 20 samples and handed over; each further workflow; and monthly Managed Ops.
What do AI prompt engineering services do?
AI prompt engineering services turn the way your team asks an AI model to write into a tested, documented system: system prompts that carry your brand voice and rules, reusable templates for each content type, worked examples, guardrails that catch errors and made-up facts, and a scoring method that shows the output is good before anyone publishes it.
What is an example of AI prompt engineering for marketing content?
A brand-voice blog template is one example. A generic prompt is a one-line request typed from memory, so every writer gets a different result; the template is a specification: the reader, what the brand may and may not say, the structure, the sources allowed, the examples to imitate and the checks to pass. It is tested on real samples.
How are AI prompts tested for accuracy and hallucinations?
Every template is run on 20 of your briefs and scored by your editors on a fixed rubric until the score holds. Hallucinations are cut, not removed: the prompt limits the model to sources you supply and asks it to flag missing facts, a guardrail step checks names, numbers and quotes, and an editor catches the rest before publication.
Who owns the prompts, the tests and the data?
You do. Prompts, examples, test sets and documentation live in your workspace and your model accounts from the first draft; ownership is written into the contract. Your brand documents and customer data stay in your systems; our offshore team works through least-privilege access, signs a data processing agreement before personal data is used, and is removed at handover.
Start with a free 30-minute scoping call or the five-day diagnostic.