What is the difference between BETTER! and OpenText Media Management?

BETTER! is an agentic AI DAM built AI-native from the first commit. Humans set the strategy and AI agents do the asset work: your team defines the taxonomy, brand voice, naming rules, and approval logic, and agents describe, enrich, and classify every asset the moment it lands, under your direction. You manage the library in plain language, and a native MCP server lets your own AI agents drive it directly. OpenText Media Management is an established enterprise platform where AI arrives as a separate add-on layered onto legacy foundations. BETTER! treats intelligence as the foundation, not an extra module: not AI-assisted, agent-operated.

Is BETTER! a good OpenText alternative for AI workflows?

Yes. With BETTER!, AI runs the library under your team's direction: autonomous ingestion agents describe, enrich, and classify assets on arrival, writing titles, keywords, and descriptions to the rules you set, plain-language commands replace clicking through screens, and your own agents can search, enrich, organize, and publish through a native MCP server and agent-ready API. It is model-agnostic across 300+ models with one key, including local and air-gapped models, so you are never locked to one vendor's AI.

Does BETTER! deploy faster than OpenText?

BETTER! self-hosts in one command or runs fully managed, with no consulting engagement required to get started. OpenText deployments are typically multi-month projects involving consultants. BETTER! is designed for your own team to run, customize, and own.

Can BETTER! understand video and run AI offline, unlike OpenText?

BETTER! understands video scene by scene and transcribes every spoken word, so you can search inside footage and jump to the exact moment something happens, rather than just storing the file. It can also run on your own local or air-gapped models, so your data and intelligence stay under your control.

BETTER! vs OpenText

Enterprise legacy with AI bolted on.
Or agentic from line one.

Humans set the strategy. Agents do the work.

OpenText Media Management is a deep, established enterprise platform, and AI arrives as a separate add-on stapled to a legacy core. BETTER! is the agent-operated AI DAM: your team sets the taxonomy, brand voice, and rules, and agents run the asset work within them. Drop a file in and agents describe and enrich it instantly, run the library in plain language, and point your own AI agents at it through a native MCP server. Intelligence isn't a module here. It's the foundation. Not AI-assisted. Agent-operated.

The Problem

AI as an add-on to a legacy core.

An agentic DAM isn't a place where files sit. It's a system where AI agents understand, organize, retrieve, and act on your assets — under your team's direction. OpenText has been in this business a long time, and its enterprise depth is real. But OpenText Media Management is a pre-AI platform, and its AI capabilities come through OpenText Magellan, a separate enterprise add-on with its own pricing. The intelligence is bolted onto a legacy foundation, so it assists at the edges; it doesn't run the library for you.

With BETTER!, agents do the tactical work and you stay in control. You define the taxonomy, the brand voice, the naming rules, and the approval logic; agents apply them at scale. Drop in 10,000 assets and they're described and enriched in the time it took to do ten: titles written, keywords applied, descriptions drafted, everything findable and on-brand. No queue, no backlog. Ask "find the unlabeled photos from the Johnson shoot and describe them" and it's done. That's a fundamentally different posture than a static AI module on an enterprise stack.

There's also the weight. OpenText Media Management is one piece of a larger content management empire, and buying it often means buying the ecosystem. Deployments run for months with consultants, customization requires professional services, and you lock to OpenText's AI with no option to bring your own models or point your own agents at the library. You're not choosing a DAM. You're choosing a platform vendor for the next decade.

The Answer

The agentic DAM. Built AI-native from the first commit.

Autonomous ingestion agents. Agents describe and enrich every asset the moment it lands. Titles, keywords, descriptions, all written for you to your team's rules. 10,000 assets organized in the time it took to do ten.
Conversational control. Manage the whole library in plain language. "Find the unlabeled photos from the Johnson shoot and describe them." Say it, it's done.
Agent-ready, not just AI-powered. A native MCP server and agent-ready API let your own AI agents search, enrich, organize, and publish directly — within the rules your team sets.
We understand your video. Scene by scene, with every spoken word transcribed, so you can search inside footage and jump to the exact moment something happens.
Use whatever AI you want. 300+ models, one key, including your own local or air-gapped models. No Magellan add-on, no vendor lock. Correct it once and it remembers.
Deploys in minutes, not months. No consultants. Your team runs it, customizes it, and owns it, self-hosted or fully managed. That's the point.

Feature Comparison

Side by side

Feature	OpenText	BETTER!
Foundation
AI posture	AI bolted onto a legacy core	Agentic, AI-native from the first commit
Deploy time	3-6 months with consultants	Minutes. One command.
Who runs it	Professional services required	Your team. Self-hosted or managed.
Agent access	No MCP server	Native MCP server + agent-ready API
AI
Ingestion	Static rules, human-driven	Autonomous. Agents catalog on arrival
Conversational control	No	Run the library in plain language
Built-in AI	OpenText Magellan (enterprise add-on)	Agentic intelligence, included
Model choice	OpenText only	300+ models, one key. Local or air-gapped too
Video understanding	Stores video	Understands it scene by scene; search inside footage
Search
Speed	Proprietary, requires tuning	Sub-50ms results, zero config
Semantic search	Limited	Find by meaning, not just keywords
Cost
Licensing	$100K-$500K+/year	Flat license, transparent
Implementation	$100K-$300K consulting	Self-service
First-year total	$300K-$1M+	Under $15K
Support	$50K+/year	Included
Security
Auth	Enterprise SAML/LDAP	JWT + SSO included
Compliance	SOC2, ISO	SOC2-ready
Audit trail	Enterprise tier	Full audit trail

Green = shipped today. Yellow = planned. Red = missing or weak. Gray = legacy or partial.

Honest Take

When OpenText makes sense

You're in a Fortune 500 that already runs OpenText Content Suite and needs deep integration between DAM and the broader content platform, which OpenText genuinely delivers
Procurement requires an established enterprise vendor with decades of track record and existing master service agreements
You have a dedicated platform team and the budget for enterprise licensing, consulting, and ongoing support contracts, and AI is not central to how you'll use the DAM

OpenText has been in this business for a long time, and its enterprise depth is real. For organizations where those factors outweigh everything else, it can be the right fit. But if you want a DAM where intelligence is the foundation, not an add-on, where agents do the tactical work and your team owns everything, there is a BETTER! option.

Is It Time?

Who should switch

Teams that want AI to actually run the library: catalog on arrival, take plain-language commands, do the tactical work autonomously, instead of paying extra for a static AI module
Organizations that want their own AI agents to drive the DAM through a native MCP server, with 300+ models or their own local and air-gapped models behind one key
Teams whose OpenText instance is maintained by consultants, not their own people, tired of writing checks for changes that should take hours, not weeks
Anyone who works with video and needs to search inside footage, not just store the file
Anyone who needs an agentic DAM, not an entire content management empire with decade-long vendor lock-in

OpenText is a trademark of Open Text Corporation. OpenText Media Management and OpenText Magellan are trademarks of Open Text Corporation. Oracle is a trademark of Oracle Corporation. SQL Server is a trademark of Microsoft Corporation. This page is an independent comparison based on publicly available information, including product documentation, published materials, and user reviews. BETTER! is not affiliated with, endorsed by, or sponsored by Open Text Corporation. All comparisons, assessments, and opinions on this page reflect the views of the BETTER! team based on publicly available information as of March 2026 and may not reflect recent changes to either product. Pricing references are estimates based on publicly available data and industry reports. Your actual costs may vary. All trademarks belong to their respective owners.

Enterprise legacy with AI bolted on.Or agentic from line one.