Customer service · MediaUse case, not a client story
Make calls, images and video searchable.
You record every call and keep every photo and video, but nobody can find anything in them. What customers said, what was promised, what a clip shows: it is all there, locked in files. We turn those files into data you can search, count and report on.
Search across every fileSchematic
⌕refund complaints, last month
CallCustomer asks about a refund, twiceRefund · Repeat contact
VideoProduct shown in the opening sceneScene · Product
ImageDamaged parcel, photo from a claimDamage · Claim
Each result opens at the exact moment, with personal details masked.
3.5×Target return in 12 months
Week 1Fixed-fee audit
6 weeksTo the first live result
3Senior people on the work
TypeUse case: what we build, not a client story
ForService teams with call recordings, and media teams with large photo and video libraries
EngagementWeek 1 audit, then build in about six weeks, fixed scope, fixed fee
Runs onSpeech, image and video models, a search index and a store in your own cloud
The problem
Thousands of hours recorded. None of it searchable.
Your systems hold neat rows for orders and tickets. The real detail sits beside them in files: the call where a customer explained the problem, the photo of the damage, the footage you shot last year. Commonly cited estimates put most of a company's data in this form. Today the only way to use it is for a person to play it back.
Every call recorded, almost none of it heard again
What was broken
Quality checks listen to a small sample of calls, so most problems are never heard.
Why customers call is guessed from ticket categories agents pick in a hurry.
Media teams search by file name and memory, and reshoot what they already have.
Recordings hold names, phone numbers and card details, stored with no masking.
None of it joins to your orders, tickets or customers, so it never reaches a report.
You might be here if
You record calls but only review a handful each week.
Your agents choose the reason for a call from a drop-down.
Finding a clip or a photo means asking the one person who remembers it.
You are unsure what personal data sits inside your recordings.
Why it mattered. The answers to why customers leave, complain or come back are already in your files. Without search, you pay to store them and never use them.
The approach
Turn every file into rows.
In Week 1 we pick the questions that matter most, such as why customers call, or which footage you own, and take a sample of real files to test against. Then we build a pipeline that transcribes calls, describes images and indexes video, masks personal details, and links each result to the order, ticket or customer it belongs to. Your people check the samples and decide what counts as right.
Every moment indexed, every clip findable
Your files
Call recordings
Photos and scans
Video library
→
woodfrog method
Transcribe and describeSpeech, image and video models
Mask personal detailsBefore anyone searches
Link and indexTo orders, tickets, customers
→
What changes
Search by meaning
Reasons counted, not guessed
Files joined to your data
Files you can actually use
Deliberately not doneScoring or judging agents automatically. People review; the data helps them.
People check the samples and decide. Models transcribe, describe and tag.schematic
The solution
A searchable layer over every file you keep.
What we build
A pipeline that picks up new recordings, photos and videos as they arrive.
Transcripts by speaker, image descriptions and video scenes with timestamps.
Masking of names, phone numbers and card details before anything is indexed.
Links from each file to the order, ticket or customer it belongs to.
A search that works on meaning, not just file names, and opens at the right moment.
Tables of call reasons, topics and media tags that feed your existing reports.
Files and results stay in your own cloud. Personal details are masked by design; we make no compliance claim, but the setup is built with the DPDP Act 2023 in mind.
How it would run
Wk 1Wk 2Wk 3Wk 4Wk 5Wk 6Wk 7
Audit
Sample of real files
Build
Transcribe, mask, link, index
Operate
Ongoing
Wk 1Wk 2Wk 3Wk 4Wk 5Wk 6Wk 7
Audit
Sample of real files
Build
Transcribe, mask, link, index
Operate
Ongoing
We start with one file type, usually calls, and add the others during the build. Operate is open-ended and drawn at one week only to fit.
The impact
What we would measure.
What each file turns intoFrom a file nobody opens to rows you can search, count and report on.
Schematic, no values
Call recording↓Transcript, by speakerTopic and reason for the callPromises made, follow-ups owed
Image↓What is in the pictureAny text in it, read outMatched to the order or claim
Video↓Scenes with timestampsSpoken words, transcribedObjects and products seen
Return over twelve monthsIllustrative shape, not a result
Audit, then build: about six weeksOperate: return tracked every month
Measured on your own numbers, the same way as the baseline. The promise is at least 3× within 12 months of delivery.
What we would measure on a real engagementWhat we would measure
Share of calls reviewedSampled by hand before, every call after
Time to find a clip, photo or callTimed on the same requests, before and after
Call reasons from transcriptsCompared with the reasons agents picked
Personal details found unmaskedChecked on samples every week
Return on the engagementTarget: at least 3.5× within 12 months, measured on your own numbers
Put your recordings and media to work.A short call, or record a message. A person replies within one business day.
