Signiant

Professional Services · Connected/Intelligence

Connected/Intelligence

Bringing applications to the content, not the content to the applications

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What It Is

Connecting content, services, and AI without movement

Most AI services available to media operations expect content to come to them — moved, duplicated, or ingested into a separate environment before anything useful can happen. This expensive and time-consuming model breaks when content lives across multiple clouds, on-prem storage, partner systems, and archives.

Signiant’s Connected/Intelligence is a different model. Through the Signiant Platform, production toolsets, AI applications, and agents like Claude, ChatGPT or CoPilot provide visibility, access, and action on content where it already lives. The platform is the connective layer. The intelligent tools are yours to choose, configure, and shape to your workflow.

It works in two parts that build on each other.

  • The connection layer brings AI applications and processes to content as Custom Actions in Media Engine — enriching your library with metadata that the rest of your tools can use.
  • The intelligence layer extends that further through a Signiant MCP Server and your AI agents, letting natural-language prompts trigger multi-step workflows across the content the platform already connects.
    • How It Works

    Independent but unified

    Each layer can be adopted on its own, but when used together, they provide a myriad of user-generated, on-the-fly workflows that speed up discovery and action without needing to pre-configure every workflow possiblity.

    Layer 01 — Connection

    AI services as Custom Actions in Media Engine

    Media Engine is the part of the Signiant Platform that connects AI services and tools to content where it already lives. Customers choose the AI services they want to use — transcription, scene detection, object recognition, content classification, rights checking — and configure them as Custom Actions that operate on content directly through the platform.
    The outputs of those services are captured and indexed. Other tools, workflows, and searches can then use that enriched metadata without duplicating content or copying it into separate analysis systems.
    This is the foundation. AI runs where content is. Metadata flows back into the platform. The library becomes more searchable, more useful, and more queryable over time.

    In Practice

    Every clip ingested this week was automatically transcribed, tagged for on-screen subjects, and indexed by scene type — without leaving the storage it was uploaded to.

    Custom Actions ran the AI services. The platform indexed the results. Nothing was moved or duplicated to get there.

    Layer 02 — Intelligence

    MCP Server and AI Agents

    For customers exploring agent-driven workflows, the Signiant Platform can act as the connection point between your AI applications and content environment, no matter where that content lives. Through an MCP Server connected to the platform, an AI agent performs multi-step operations from natural-language prompts.

    The agent doesn’t see raw files. It sees the platform. The platform sees the content. The agent reasons against indexed metadata to know what content exists, where it lives, what’s been done to it, and what to do next — then it acts.

    The result is user-generated custom workflows on the fly. A producer or operator describes what they want in plain language, and the agent assembles the steps to make it happen through the same platform that already governs how content moves and who can access it.

  • Natural Language Prompt. Agent Ready

    • “Pull every clip from Saturday’s game where the home team scored, prep them for review, and notify the producer when they’re ready.”

  • Send to Agent

    • The agent searches indexed metadata, identifies matching clips, triggers any required processing, queues the results, and sends the notification — operating through the platform across distributed content.

    Why They Compound

    Visibile, accessible, & actionable metadata

    An AI agent reasons against what it can see. If the library is rich with metadata, the agent has material to work with. If it isn’t, the agent has thin ground to stand on. That’s why most customers building toward Connected/Intelligence start with the connection layer first.

    Layer 01

    Custom Actions enrich the library

    AI services run on content as it moves through the platform, building a metadata foundation across distributed storage.

    Layer 02

    AI Agents reason against it

    Natural-language prompts work because the library knows what content exists, where it is, and what’s been done to it.

    The two layers run independently, but unify your content operations. Custom Actions provides the link AI Agents need to be useful — which is why the practical path for most customers is to establish the connection layer first, then layer in agent capability as the metadata foundation matures.

    Where Professional Services Comes In

    Design to work for you

    The Signiant Platform provides the layer to connect and use AI services; Signiant’s MCP Server enables easy, agent-driven workflows, making your AI investments instantly operational.

    What turns those capabilities into operational impact for Signiant customers is the design work, using your own toolsets you’ve invested in to connect content, defining the metadata schema your workflows actually need, configuring the integrations, and tuning the agent behavior to your team’s working patterns.

    Signiant Professional Services brings that work, and the engineering experience that turns Connected/Intelligence from a model into a working part of your operation.

    What Engagements Include

  • Connecting AI Applications through Custom Actions in Media Engine
  • Metadata schema design and harvesting strategy
  • MCP Server setup and configuration on the Signiant Platform
  • The connective architecture that ties everything into a working environment

    • Bring Connected/Intelligence into your operation.

    Start with a scoping conversation. Walk through what content you have, what AI services you want to use, and what your team is trying to do — and the team will outline what a Connected/Intelligence engagement looks like for you.

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