Media & Entertainment · Broadcast compliance monitoring
Banao builds AI that checks every frame and every ad break before playout — content ratings, profanity, ad-insertion timing, watermarks, and regional cut rules — and flags what needs human review instead of reviewing everything by hand.
The system runs against your existing playout schedule and MAM. When something fails a check, it surfaces in the compliance queue with a timecode and a reason, not a regulator's notice three days after air.
Broadcast compliance is not one problem. These are the checks that catch fines and complaints before they happen.
The model reads scene content — violence, adult themes, drug references — against your regulatory rating thresholds and flags anything scheduled above its watershed slot before the programme leaves the queue.
Every ad break is checked against the schedule and SCTE-35 markers for timing, separation rules, and product category conflicts before the signal leaves the facility.
Frame-level checks confirm that mandatory channel and rights-holder watermarks are present throughout the required windows — no silent dropout goes to air undetected.
Rights windows, territorial versioning, and per-region regulatory cuts are enforced at playout rather than relying on a coordinator to catch the wrong version in the schedule queue.
Subtitle and caption files are checked for coverage, timing, and language accuracy against the programme schedule before air — accessibility obligations, not just broadcast guidelines.
Every check, every flag, and every override is stored with timecode, reason, and reviewer identity — so your compliance report writes itself and regulator requests are answered in hours.
Numbers shown dotted (··) are being verified in our case-study metrics pack — published only when confirmed.
Times Internet
Times Internet publishes video across news, entertainment, and sports properties in India. Banao deployed automated pre-publish content rating and ad-placement checks, replacing a manual queue that grew faster than the team could staff.
A regional broadcast network
A regional broadcaster reviewed ad breaks and watershed schedules by hand across two feeds. Banao wired automated SCTE and content-rating checks into the playout workflow, so the compliance team handles flagged exceptions rather than scanning every minute of scheduled output.
Banao runs a ~300-person engineering operation on its own AI before any client sees it. InterviewGod screens our hires. Vikaas runs our demand generation pipeline. Both have to survive production use inside Banao before they reach a customer.
A compliance system that has never had skin in the game is a prototype. We hold every system we build to the same standard we hold our own — because we know what production use actually costs when something slips through.
We build compliance systems because the cost of manual review is real. But AI compliance is not the right first step for every operation:
We do not quote a compliance deployment off a requirements document. We start by mapping where violations are actually escaping.
We audit a sample of your recent output against your regulatory obligations, map where violations are going undetected, and hand back a ranked list of checks to automate with ROI maths behind each — yours to keep regardless of whether you continue. Proceed, and the Sprint cost is credited against the build.
Check models trained to your regulatory framework and house rules, integrated with your MAM, playout schedule, and SCTE infrastructure. The compliance queue UI and incident log are part of the deliverable.
Live deployment with reviewer override, incident logging, and a compliance dashboard. Regulator requests, override patterns, and missed-flag feedback sharpen the checks over time.
Which regulatory frameworks does the AI cover?
The check rules are configurable — we implement them against your specific regulator's requirements, whether that is OFCOM, TRAI, FCC ad-scheduling rules, or a house standard. The model does not ship with a generic ruleset; we build to your obligation list during the Discovery Sprint.
Can the system handle live broadcast as well as pre-recorded content?
Pre-recorded and scheduled content is the primary use case — AI checks run before the signal leaves the facility. Live broadcast compliance requires a separate real-time architecture with higher latency constraints. We scope them differently and will tell you which applies to your problem.
How do reviewers stay in control when the AI flags something?
Every flag surfaces in a compliance queue with a timecode, a check description, and a confidence level. Reviewers confirm, override, or escalate — and every decision is logged with a reason. The AI reduces what the team has to watch; it does not make the call.
Does it replace our compliance team?
No. The system handles the high-volume scanning pass so your compliance team focuses on flagged exceptions and regulator correspondence rather than watching every minute of scheduled output. Headcount is freed for judgement work, not removed.
What does integration with our MAM and playout system look like?
We integrate with your existing MAM and playout schedule via API or file-based handoff — legacy formats included. The compliance check runs before the asset reaches the transmission queue, and the outcome writes back to your schedule metadata. Integration scope is confirmed during the Discovery Sprint.
Bring one week of post-air incidents or a recent regulator notice. In 45 minutes we will map which checks should be automated and what that would cost.
Book a 45-min scoping call
