AI content agents that generate good content, not AI slop.
Custom AI agents for content generation — briefs, drafts, social, ads, product descriptions. Grounded in your brand voice and your real data, not generic AI output.
Generic AI content is everywhere and it's already worthless.
ChatGPT-default copy is recognizable from a hundred feet away. Lists of three. Em dashes everywhere. The same generic phrasings. Search engines, social platforms, and audiences are already filtering it out.
Generic AI writing tools (Jasper, Copy.ai, Writer) produce more of the same. Their default style is the average of internet writing — fine for the 80% case, useless when you need content that actually represents your brand.
Content agents trained on your voice and your data.
We build content agents that know your brand voice (trained on your existing best content), your product facts (pulled from real sources, not made up), your customer language (extracted from real conversations), and your channel constraints (length, tone, format per channel).
Output is high-quality drafts your team edits — not auto-published slop. Time spent on content goes down 70%; quality stays at or above your current bar.
The shape of capabilities we build into agents for this use case. Yours may need a subset; we scope in discovery.
Brand voice fine-tuning
Train the agent on your existing best content. Voice consistency across blog, email, social, ads. No generic AI style drift.
Brief → draft workflow
Brief in: target keyword, angle, audience, format. Draft out, grounded in your knowledge base. Reviewed by humans, edited, shipped.
Product descriptions at scale
Generate consistent product descriptions for thousands of SKUs, pulling specs from your PIM. Different versions for different channels (Amazon, Shopify, retail partners).
Social variants
One source brief → variants for LinkedIn, X, Instagram, TikTok, each formatted for that channel's norms. Hashtag and emoji conventions per channel.
Ad copy + variants
Hundreds of ad variants for testing — headlines, descriptions, CTAs — each grounded in your value props and offer.
Email sequences
Multi-touch sequences with branching by segment. Subject lines tested. Tone matched to segment lifecycle stage.
Blog drafts
SEO-aware blog drafts with structure, sources, internal linking — reviewed and finished by humans before publish.
Fact grounding (RAG)
Agent answers from your real product docs, support articles, and approved sources. No made-up claims.
Voice + plagiarism guardrails
Output checked against your style guide and existing content. Duplicate content detection. AI-detection scoring before publish.
How the agent ships.
Same structure for every agent build. Predictable timelines, fixed scope.
- 01
Discover
1 week. Real workflow, real data, what 'good' looks like. We pick what the agent owns and what humans keep.
- 02
Architect
1 week. Tool inventory, model choice, memory strategy, escalation rules, eval criteria — written and reviewed.
- 03
Build MVP
2–3 weeks. Working agent handles the happy path against real data. Observability and human-review UI from day one.
- 04
Harden
2–4 weeks. Edge cases, evals, monitoring, training, gradual rollout. Production-ready.
- 05
Run
Optional retainer. Model upgrades, prompt tuning, new tools, scope expansions.
The architecture you'd be getting.
Search engines penalize low-quality AI content — the generic, ungrounded, no-value-added stuff. They don't penalize AI-assisted content that's accurate, well-written, and serves the searcher. Most of the AI content getting penalized is auto-published with no human editing. We're explicit: this is for drafts your team edits and approves.
RAG against your real sources — product docs, knowledge base, approved materials. Structured outputs that force citations. Fact-extraction step where the agent extracts claims and flags any unsupported ones for human review.
Yes — with enough source material. We use your existing best content as training examples (in-context or fine-tuned) and a documented style guide for explicit rules. Voice consistency is the main thing custom agents do better than generic tools.
Built-in checks. Output compared against your existing content (avoid self-duplication) and the open web (avoid accidental plagiarism). Flag-and-rewrite before publish.
Model API costs are low for content workloads — typically $100–500/month for an active content operation. The value is in compressed creator time. Most clients see 70%+ reduction in time-to-publish while maintaining or improving quality.
Want a content generation agent for your team?
Tell us the workflow, the volume, and the systems involved. We'll come back with what we'd build, how it would handle the edge cases, and a fixed quote.