AI Use Case
AI for Content Workflows
Speed up content operations with template-governed drafting, QA checks, and approval-aware publishing workflows.
Problems
What’s slowing teams down
Common bottlenecks we see before AI workflows are implemented.
Slow content production
Teams spend time drafting and editing repetitive formats.
Inconsistent quality
Style and compliance vary across authors and channels.
Approval bottlenecks
Publishing gets stuck without structured review workflows.
Fragmented tools
Docs, CMS, and workflow tools don’t stay in sync.
Delivery
What we deliver
Implementation-ready modules designed for reliability, safety, and real operations.
Template-governed drafting
Draft within controlled templates and style rules.
QA and review workflows
Checks for policy, tone, and formatting with review queues.
Approval-aware publishing
Automations that respect approvals and audit logs.
Metrics and iteration
Track outcomes and improve workflows over time.
Deliverables
What you’ll get
Concrete outputs designed for predictable handoff and measurable improvements.
Drafting assistant with templates and style rules
QA checks + review workflow
Publishing automation (as needed)
Approvals and audit logs
Monitoring and metrics
Handoff documentation
Process
How we work
A pilot-first approach, with the quality and governance needed for production rollouts.
Define
Templates, style rules, and approvals.
Build
Drafting + QA + routing workflows.
Launch
Monitoring and iteration plan.
Stack
Suggested implementation stack
A practical stack we can adapt to your constraints and existing systems.
Automations
Example automations
A few workflows that usually deliver ROI quickly.
Draft generation with templates
QA checks and review routing
Publishing automation after approval
Content repurposing workflows
Start Small
Start small in 7 days
Three pilot-friendly options that reduce risk and ship value fast. Choose one, share access, and we deliver a production-ready baseline.
Standard
AI delivery standard
Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.
Logging + tracing
Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.
Guardrails + safety
Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.
Evals + regression tests
Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.
Cost + latency controls
Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.
Documentation + handoff
Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.
Security-first integration
Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.
Pricing
Typical pricing ranges
We confirm scope before starting. These ranges help you plan a pilot versus a full rollout.
Pilot workflow: $900–$3,500
Multi-channel ops: $2,500–$9,000
Timelines
Delivery timelines
Common timelines for pilots and production hardening, depending on integrations and governance.
Pilot: 1–2 weeks
Expanded rollout: 2–4 weeks
Risks
Risks & mitigation
The failure modes we design for so reliability and trust stay high.
Off-brand outputs
We enforce templates and style rules, and support review queues for sensitive content.
Publishing mistakes
We add approvals, audit logs, and safe defaults for automation.
AI Case Examples
Micro case studies (anonymous)
A few safe examples of outcomes we build for real operations—no client names, just results.
Secure Mobile Solution in Australian Defence Ecosystem
Problem: Secure data workflows were required in a regulated environment with strict access controls.
Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.
Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.
AI Knowledge Base Across 2,000+ Pages
Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.
Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.
Outcome: Reliable answers with <10s response times and measurable improvements on real queries.
Ops Automation with AI + n8n
Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.
Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.
Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.
Relevant Gigs
Start with a fixed-scope gig
Pick a gig to launch a pilot quickly with clear deliverables and timeline.
Compare
Decision guides
Quick comparisons to help you choose the right approach before building.
Related Services
Explore deeper implementations
When you need more depth than a pilot, these services cover full delivery.
Explore
More AI pages
Additional pillars and use cases to help you plan your roadmap.
FAQ
Frequently asked questions
Can this enforce our style guide?
Yes. We implement template governance and QA checks to keep outputs on-brand.
Can we require approvals before publishing?
Yes. Approval gates are a common pattern for safer automation.
Which tools can it integrate with?
We can integrate with CMS, docs, and workflow tools depending on APIs and access permissions.
Do you support review queues?
Yes. We add review queues for sensitive content or low-confidence outputs.
How fast can a pilot ship?
A single workflow pilot typically ships in 1–2 weeks once templates and approvals are agreed.
Do we own the workflow code?
Yes. Source code and handoff notes are included.
Want an AI pilot for your workflow?
Start with a fixed-scope gig or request a tailored implementation plan for your systems.