AI Services
Generative AI
Custom generative AI applications for content, product and workflow use cases, built on current commercial models.
Definition
What is Generative AI?
Generative AI refers to AI models that produce new content — text, images, code or other output — based on a prompt or input, built on large language models and related architectures. Generative AI services cover designing and building applications that use these models for a specific business purpose.
Who It’s For
Businesses with a specific content, product or workflow use case that a generative AI application could meaningfully speed up or improve — not businesses looking for AI for its own sake.
Problems This Solves
- Content or drafting work consumes disproportionate team time for its value.
- Internal teams experiment with generic AI tools without a scoped, integrated application.
- A specific product feature idea involves generative AI but hasn’t been scoped or built.
Our Approach
We scope the specific use case first, select the model and architecture suited to its accuracy, cost and latency needs, and build it as an integrated application — not a one-off prompt experiment.
What You Receive
- Use-case scoping and model selection
- Prompt engineering and output-quality evaluation
- Application build and integration
- Guardrails for accuracy, tone and safety
- Deployment and monitoring setup
Where This Fits
- An internal tool that drafts first-pass content for human review and editing.
- A customer-facing feature that generates personalized output from user input.
- A workflow that summarizes or extracts structured data from unstructured text.
Who It's For
Built for teams that need this to actually work.
Growing Teams
Businesses scaling past the point where ad-hoc effort is enough.
Established Brands
Organizations that need a more connected, accountable partner.
AI-Curious Leaders
Teams that want AI and automation applied to real outcomes, not experiments.
The Problem
What usually goes wrong.
- Efforts are disconnected from measurable business outcomes.
- No single owner is accountable for the result.
- Execution lags behind strategy by months.
Our Solution
How Dmedia approaches it.
We scope generative ai against your actual goals, connect it to the rest of your growth system, and stay accountable to outcomes — not just deliverables.
Capabilities
What's inside this service.
Strategy & Audit
A clear-eyed read of where things stand today and what's realistic to improve.
Execution
Hands-on delivery from a team that also builds the systems around it.
Measurement
Reporting tied to the metrics that actually matter to your business.
Process
How we deliver it.
Discover
Audit, benchmark and align on goals.
Plan
Scope the work and define milestones.
Build
Execute with regular checkpoints.
Launch
Ship and validate against goals.
Optimize
Iterate using real performance data.
Deliverables
What you actually receive.
- A documented strategy and roadmap
- Implementation across the agreed scope
- Reporting against agreed metrics
- A named point of contact throughout
Technology
Tools we work with.
Use Cases
Where this fits.
Launching Something New
A product, market or offer that needs a credible first push.
Fixing an Underperformer
An existing effort that isn't producing the results it should.
Scaling What Works
A proven channel or workflow that needs to run at higher volume.
Illustrative Example
How this plays out against industry benchmarks.
Illustrative methodology walkthrough — not a claimed result for a specific unnamed client.
6.64%
Average Google Ads CTR (all industries) — WordStream, 2026 Google Ads Benchmarks
The mechanism we'd use to move a client toward — or past — this industry average combines the capabilities above with continuous measurement.
Frequently Asked Questions
Which AI models do you build on?
We select from current commercial large language models, including OpenAI's and Anthropic's Claude models, based on which best fits the specific use case's accuracy, cost and latency requirements.
Will the output need human review?
For most business use cases, yes — we design generative AI applications with human review built into the workflow rather than positioning them as fully autonomous by default.
How do you handle accuracy and hallucination risk?
Through a combination of prompt design, retrieval-based grounding where relevant, output evaluation, and clear guardrails on what the system is and isn't allowed to assert.
Can this integrate with our existing tools?
Yes, generative AI applications are typically built to integrate with your existing CMS, CRM or internal tools rather than as a standalone destination.
Ready to talk about Generative AI?
Tell us where things stand today and we'll scope a plan around it.