Visual Detection
Identifies configured objects and visual classes and associates detections with locations and timestamps.
Media Archive Search and Discovery
AI Video Search Engine for Media Archives
Search inside video using scenes, objects, speech, on-screen text, topics, people, and business metadata—not filenames alone. Mimasa AI combines computer vision, multimodal understanding, semantic retrieval, analytics, and agentic workflows to make large media libraries easier to explore and activate.
Find a programme, clip, or exact moment through natural-language questions and structured filters. Then ask an AI agent to prepare a collection, route a review, generate an archive report, or initiate an approved downstream workflow.
For broadcasters, OTT platforms, studios, production houses, publishers, sports-media teams, and enterprise content owners. See our wider work on AI for Media & Entertainment.
The Problem
Find the Right Moment Without Watching Every File
Valuable media is often difficult to reuse because its meaning remains locked inside video and audio. Filenames, folders, and short descriptions rarely capture every speaker, topic, object, location, brand, or visual event within an asset.
Teams may know that relevant footage exists without knowing where it is stored or when the moment appears. Manual archive research becomes slower as libraries grow, while inconsistent metadata limits conventional keyword search.
Mimasa turns media analysis into AI-powered video search. It connects archive assets and related data, creates timestamped intelligence, and allows authorised users to retrieve relevant results using natural-language descriptions, semantic similarity, transcripts, visual detections, metadata, and filters.
Search becomes the start of the workflow. Mimasa can analyse results, build reports, assign reviews, notify teams, or trigger governed actions after the right content is found.
Definition
What Is an AI Video Search Engine?
An AI video search engine searches the content within video rather than relying only on file names or manually entered tags. It can use visual objects, scene descriptions, spoken words, transcript entities, on-screen text, timestamps, and existing business metadata to determine which assets or moments match a request.
Multimodal Understanding
Interprets wider context across frames, scenes, transcripts, OCR, topics, actions, and relationships.
Mimasa structures these outputs for semantic and filtered retrieval. A user can search with an everyday description, refine the results with authorised metadata, inspect the supporting moment, and initiate an agentic workflow without moving between disconnected tools.
Capabilities
Search Video Through Multiple Signals
Search by Meaning and Context
Describe the concept, activity, atmosphere, or situation you need. Multimodal understanding helps retrieve semantically relevant moments even when the query does not exactly match a transcript or manually assigned tag.
Search by Objects and Visual Evidence
Use visual detections to find configured objects, people, logos, products, vehicles, equipment, or other trained visual classes. Combine visual evidence with date, source, programme, language, or status filters.
Search Speech and Transcripts
Find spoken words, subjects, speakers, names, organisations, locations, and other entities across time-aligned transcripts. Open the result at the relevant point rather than reviewing the entire asset.
Search On-Screen Text
Retrieve moments containing titles, captions, graphics, credits, signage, product text, or other OCR-extracted information where the processing workflow supports it.
Search Exact Clips and Moments
Use video clip search to find scene- or timestamp-level results. Review the surrounding context, save the relevant segment reference, and route it into an approved collection or production workflow.
Search With Structured Filters
Combine semantic relevance with authorised fields such as content type, collection, date, source, language, territory, approval status, contributor, or rights information when those fields are available.
The metadata behind these signals is created by Media Content Intelligence and structured with Data Extraction.
Workflow
How Mimasa AI Video Search Works
Connect Media and Archive Data
Connect approved object storage, media asset management systems, content platforms, databases, APIs, document sources, and archive repositories. Preserve source identifiers and the relationships between videos, transcripts, metadata, and supporting records.
Analyse Content With Multimodal AI
Apply computer vision for configured visual detections and multimodal AI for scene and context understanding. Coordinate transcript processing, OCR, metadata extraction, and other approved analysis steps where the use case requires them.
Create Searchable Intelligence
Structure scenes, timestamps, detections, transcript segments, entities, topics, descriptions, and business fields. Validate required values and preserve references to the supporting source.
Search Naturally and Precisely
Ask a question or describe the required footage. Combine semantic results with exact transcript matches, detected visual elements, and structured filters. Inspect why a result matched and open the relevant moment.
Activate an Agentic Workflow
Ask an authorised agent to assemble results, prepare a summary, create a task, route a review, notify a team, update a connected system, or include approved findings in a report or dashboard.
Agentic Automation
From Search Results to Agentic Action
Most search experiences stop after returning links. Mimasa combines AI content discovery with agents and workflow automation so teams can continue from a relevant result to a controlled business outcome.
Create Review Collections
An agent can gather matching assets or moment references, remove obvious duplicates, organise the results against defined fields, and assign the collection to an editor, producer, researcher, or archivist.
Agentic Workflow AutomationMonitor Incoming Content
An agentic workflow can watch an approved source for new media, run the relevant visual and multimodal analysis, validate required metadata, and make processed assets available for authorised search.
AI AgentsRoute Exceptions
If a result is uncertain, missing a required field, or covered by a defined policy, Mimasa can create a review task and retain the decision before any downstream action occurs.
Generate Archive Intelligence
Turn authorised search results into collection summaries, research briefs, content inventories, operational reports, spreadsheets, dashboards, or presentations.
Data Visualisation and DashboardsCoordinate Reuse Workflows
After a team selects footage, an agent can retrieve available supporting information, check required workflow fields, request approvals, notify stakeholders, and prepare the next task. Rights, licensing, editorial, or compliance decisions remain with authorised reviewers.
Media Teams
A Content Discovery Platform for Media Teams
Mimasa supports different discovery needs without forcing every team to search in the same way.
Broadcasters and Newsrooms
Find prior coverage, interviews, people, places, statements, and visual sequences across programmes and footage libraries. Prepare research collections and route selected results into editorial review.
OTT and Streaming Platforms
Explore programmes, episodes, promos, clips, transcripts, and catalogue information through semantic queries and structured filters. Support catalogue operations and internal discovery rather than consumer recommendation.
Studios and Production Houses
Retrieve locations, props, scenes, dialogue, contributors, and reusable visual material across approved production archives. Connect selected results with human-led production workflows.
Sports Media Teams
Search recorded footage for configured players, objects, sponsors, actions, commentary, or match context. Review relevant moments before using them in editorial or production outputs.
Publishers and Digital Media Teams
Find relevant video, audio, transcript, and image material for research and authorised reuse. Build collections around topics, events, people, or organisations.
Archive and Library Teams
Improve access to legacy collections with incomplete metadata. Use AI to propose searchable information while preserving source records, reviewer decisions, and existing catalogue authority.
Natural Language
Example AI Video Search Questions
“Find interviews where renewable-energy investment is discussed.”
“Show factory footage containing robotic arms and workers wearing safety equipment.”
“Find every approved clip in which this product appears with its logo visible.”
“Show scenes of heavy rainfall near a city transport hub.”
“Find the exact moment the spokesperson discusses the acquisition.”
“Show Hindi-language clips from 2025 about electric vehicles.”
“Which archived programmes mention this organisation in speech or on-screen text?”
“Create a review collection from the matching clips and assign it to the editorial team.”
The final example deliberately shows the shift from retrieval to agentic workflow automation.
Analytics
Ask Questions Across the Archive
Video question answering allows an authorised user to ask a question about processed media and receive an answer grounded in available scenes, transcripts, detections, and metadata. Mimasa links the response to supporting assets or timestamps wherever the retrieval configuration supports it.
Search finds the relevant media. Analytics explains patterns across it. Agents coordinate what happens next. Explore Data Visualisation and Dashboards.
- How much processed content covers a particular subject?
- Which entities or visual classes appear most frequently?
- Which collections contain incomplete or unapproved metadata?
- What proportion of incoming media has completed analysis?
- Which search topics are increasing across authorised teams?
- Which assets or collections are being retrieved for reuse?
Integration
Work With Existing Video Archive Software
Mimasa is an intelligence, search, analytics, and automation layer. It does not need to replace the systems that already store, catalogue, manage, publish, or preserve media.
Connect approved sources through available APIs, databases, object storage, repositories, or secure data pipelines. Depending on the target system and permissions, Mimasa can read assets and metadata, store derived intelligence, return source references, initiate reviews, or write approved information back.
Media asset management and digital asset management systemsVideo archive software and preservation repositoriesContent management and OTT catalogue platformsCloud or on-premise object storageData warehouses, databases, and analytics environmentsWorkflow, task, notification, and approval systems
Governance
Govern Search, Content, and AI Actions
Media archives can contain unreleased content, licensed material, personal data, contracts, confidential footage, and commercially sensitive assets. Search permissions must respect more than simple keyword relevance.
Mimasa can apply enterprise controls around which sources a user or agent may access, which fields can be searched, which models may process the content, what an agent can do, and when a person must approve the next step.
Role-based access to workspaces, sources, assets, searches, and actionsHuman approval checkpoints for defined workflowsAudit trails for analysis, retrieval, reviews, and agent actionsConfigurable confidence thresholds and exception handlingLineage from a result back to the source asset and available timestampCloud, private-cloud, and on-premise deployment optionsModel and workflow selection aligned with operational requirements
Specific retention, residency, privacy, rights, and security requirements are confirmed during solution design. Read more about Data Governance.
Business Benefits
What Media Teams Gain
Find Relevant Footage Faster
Search by meaning, visual evidence, speech, text, timestamps, and metadata instead of relying on filenames alone.
Unlock Underused Archives
Make legacy and long-form content easier to explore even when its original metadata is incomplete.
Connect Discovery to Work
Move from a result to a review, collection, report, task, notification, or approved system update through agentic workflows.
Improve Research Consistency
Give authorised teams a shared search and evidence experience across connected collections and content types.
Analyse Patterns Across Content
Use structured intelligence to understand archive composition, appearances, themes, processing status, and authorised usage.
Preserve Human Control
Apply roles, permissions, thresholds, approvals, and audit trails to sensitive content and consequential actions.
Why Mimasa AI
Search, Analytics, and Governed Automation Together
Visual Detection and Multimodal Understanding
Computer vision detects configured visual classes. Multimodal AI interprets wider scene and content context. Mimasa combines the outputs with transcripts, OCR, metadata, and business records.
Search Plus Analytics
Retrieve individual assets and moments, then analyse patterns across the authorised archive using natural-language questions, dashboards, reports, and reusable datasets.
Search Plus Agentic Automation
Use agents to monitor sources, prepare results, validate required information, route reviews, generate reports, and coordinate downstream actions.
Enterprise Governance and Deployment
Control access and agent actions through RBAC, approvals, audit trails, and deployment choices across cloud, private-cloud, or on-premise environments.
Designed Around Your Archive
Configure taxonomies, fields, filters, models, prompts, confidence thresholds, and workflows around the organisation's content and operating process.
Frequently Asked Questions
Common questions about AI video search, content discovery, and governed archive workflows.
Find the Content. Understand the Context. Automate the Next Step.
Start with one representative archive and one valuable discovery workflow. Define the queries, visual classes, metadata, permissions, review rules, integrations, and success measures before expanding across the wider media library.
Monitoring live cameras instead of archives? See AI Video Analytics.