Marketing agency · Toronto, Canada
Fazis Productions: AI content engine and creator-pipeline workflows.
Fazis Productions Toronto case study: AI content engine and creator-pipeline workflows that 10×'d asset output with the same team.
Updated 2026-05-18
- Client
- Fazis Productions
- Region
- Toronto, Canada
- Focus
- Marketing agency
The challenge
Fazis Productions runs a Toronto agency model where output scaled linearly with team hours. Every client retainer required raw footage ingestion, transcription, cut-down selection, hook variants, thumbnail copy, captions, vertical reformats, and platform-specific publishing — across YouTube, IG Reels, TikTok, and LinkedIn. The repetitive parts of post-production were the bottleneck, and the only lever to scale revenue was hiring more editors.
The build
consultance.ai built an end-to-end content engine sitting on top of the agency's creative workflow. Raw footage drops into a watched folder; the pipeline auto-transcribes, identifies high-retention moments, generates hook variants and thumbnail copy, drafts captions per platform, and reformats to vertical with safe-zone framing. A creator-pipeline layer manages the per-client style guide (tone, banned phrases, brand colors, font stack) so output stays on-brand without manual QA on every asset. Editors stop doing template work and move to creative direction, review, and the 20% of cuts that need a human eye. Output goes into a publish queue with platform-specific scheduling.
Evidence from the work
- Public Toronto marketing agency with active Instagram and LinkedIn presence.
- Public proof post on Instagram referencing the workflow uplift.
- Per-client style-guide engine enforces tone, banned phrases, brand assets across every output.
- Watched-folder pipeline runs transcript → moments → hooks → thumbnails → vertical reformat end-to-end.
- Repeatable agency content workflow built on consultance.ai's AI stack.
The outcome
- Asset pipeline output up 10× with same headcount
- Per-client style guides enforced automatically across every asset
- Editors moved from template work to creative direction and review
- Multi-platform output (YT / IG / TikTok / LinkedIn) from one source pipeline
- Repeatable production workflow that scales revenue without scaling payroll
Recorded impact
Time Saved
50h of 60h
Operator hours reclaimed every week after the system went live.
Efficiency
90% of 100%
Throughput uplift on the workflows we automated end-to-end.
System Score
92 of 100
consultance.ai readiness rating across stack, ops, and observability.
Figures from the existing case-study record; the readiness rating is Consultance’s internal assessment.
Explore a similar workflow
Start with the build library, or discuss how this approach could fit your team’s environment.