TLocal — On-Screen Text Localization for Global Content Distribution

The Problem

Every frame of film or animation that contains visible text — signs, titles, labels, graphics, legal copy — must be identified, translated, and visually verified before a title can ship to a new market. Today this work is almost entirely manual:

Compliance teams scrub footage frame-by-frame to log every instance of on-screen text, recording timecodes and screenshots into spreadsheets.
Localization coordinators copy those spreadsheets to regional language vendors, who translate in isolation with limited visual context.
Art and compositing teams mock up each translated string on the original frame in Photoshop, then route stills back for approval.
Project managers chase status across email threads, shared drives, and disconnected review tools.

For a 90-minute animated feature shipping to 5 markets, a studio typically catalogs 200–400 on-screen text instances. The manual detection pass alone takes 40–60 hours. End-to-end, a single title's text localization cycle runs 6–10 weeks and costs $80K–$150K across internal labor and vendor fees.

The Solution

TLocal replaces the spreadsheet-and-email pipeline with a single browser-based workspace powered by AI video analysis.

Step	What TLocal does	What it replaces
Detect	Uploads the video, runs OCR + temporal tracking via Amazon Bedrock, and returns every text instance with in/out timecodes, bounding boxes, confidence scores, and frame thumbnails — in under 30 seconds.	40–60 hrs of manual frame-by-frame logging.
Review	Admin reviews a sortable, filterable ticket table. Edits text, assigns actions (Translate / Edit / Ignore), adds strategy notes, and confirms each entry. Undo/redo, bulk confirmation, and multi-format export (Excel, CSV, JSON) are built in.	Spreadsheet wrangling, screenshot pasting, email review chains.
Translate	Each language team opens their own workspace with full context: frame, timecodes, detected text, action, strategy, and notes. AI-generated translation suggestions pre-fill each row. Teams edit, then preview the translated text composited onto the actual frame via NanoBanana — no Photoshop round-trip.	Decontextualized translation in isolation + manual Photoshop mockups per string per language.
Approve	Language teams confirm each translation. Admins monitor real-time progress dashboards across all 5 teams, drill into any workspace, and export final deliverables only when every string in every language is confirmed.	Status-chasing across email, Slack, and shared drives.

Quantified Impact for a Mid-Size Animation Studio

Target customer profile: Studio producing 4–6 animated features or series per year, distributing to 5+ language markets. Current localization headcount: 2 coordinators, 1 compliance reviewer, outsourced translation vendors.

Metric	Before TLocal	With TLocal	Delta
Text detection time per title	40–60 hours	< 1 minute (AI) + 2–4 hrs review	~93% reduction
Translation cycle (all 5 languages)	4–6 weeks	1–2 weeks	~70% faster
Mockup creation per string	15–20 min (Photoshop)	< 10 sec (NanoBanana)	~99% reduction
Coordinator hours per title	80–120 hrs	15–25 hrs	~80% reduction
Cost per title (labor + vendor)	$80K–$150K	$20K–$40K	~$60K–$110K saved
Annual savings (5 titles)	—	—	$300K–$550K
Time-to-market per new territory	6–10 weeks	1–3 weeks	Ship 4–7 weeks sooner

Why It Matters Beyond Cost

Local teams keep creative control. Translators see the frame, the context, and the strategy — they make culturally informed decisions, not blind string swaps.
Language is a marketing strategy. Faster, higher-quality localization lets smaller studios reach global audiences that were previously only accessible to major distributors.
Compliance risk drops. Automated detection with confidence scoring ensures nothing is missed. Every decision is tracked, exportable, and auditable.
The admin never loses visibility. Real-time dashboards replace status meetings. Export is blocked until every string is confirmed — nothing ships incomplete.

TLocal: Detect every word. Translate with context. Ship to the world.