On February 5, 2026, Anthropic released Claude Opus 4.6. It is a significant update to their flagship AI model, and it brings capabilities that matter directly to anyone working with enterprise document management.
This is not a paradigm shift or the dawn of a new era. It is a solid step forward in what AI agents can practically do with documents, spreadsheets, and enterprise content. For organizations running SharePoint, Nextcloud, Documentum, or other DMS platforms, the update opens real efficiency gains — if you know how to apply them.
What Opus 4.6 Brings to the Table
One Million Token Context Window
Previous Opus models processed 200,000 tokens, roughly 500 pages of text. Opus 4.6 extends this to one million tokens in beta — approximately 750,000 words.
For document management, this is the most relevant upgrade. A model with this context window can hold an entire migration scope, all source metadata, target mappings, and exception rules in a single working session. No chunking, no summarization loss, no context switching between batches. You describe the full picture, and the model reasons across it.
On the MRCR v2 benchmark, which tests retrieval accuracy in large contexts, Opus 4.6 scored 76% compared to 18.5% for Sonnet 4.5. This is the difference between a model that accepts large inputs and one that actually finds what you need inside them.
Agent Teams
Claude can now split a task across multiple parallel agents, each handling a piece and coordinating with the others. Combined with Cowork, the desktop agent Anthropic launched in January 2026, this means non-technical users can describe an outcome — "audit these three SharePoint sites for retention policy compliance" — and let multiple agents work on it simultaneously.
For document-heavy operations, parallel execution is practical. An agent team can review a document library, flag exceptions, draft a summary report, and prepare remediation steps concurrently rather than sequentially.
128,000 Token Output
Previous output limits forced the model to break large deliverables into multiple requests. Opus 4.6 can generate up to 128,000 tokens in a single response — roughly 96,000 words. A complete migration plan, a full compliance report, or a complete set of metadata mapping documentation can be produced in one pass.
Adaptive Effort Controls
The model now adjusts its reasoning depth based on task complexity, and developers can set explicit effort levels. A simple document classification task does not need the same computational investment as a regulatory compliance analysis. This means organizations can optimize for cost without sacrificing quality where it matters.
Context Compaction
A beta feature that lets the model summarize its own older context during long-running tasks. For multi-hour operations like processing an entire document library or conducting cross-reference analysis across thousands of files, compaction prevents the model from losing track of earlier work.
The Office Integration Layer
Opus 4.6 arrives alongside expanded integrations that make Claude a practical participant in daily document work.
Claude in PowerPoint launches in research preview, integrating directly into PowerPoint as a side panel. The model reads existing layouts and fonts to match corporate templates — useful for generating stakeholder presentations from migration data or compliance findings.
Claude in Excel receives substantial upgrades for working with spreadsheet data, formulas, and analysis directly within Excel. For metadata inventories, permission matrices, and content type mappings, this turns Excel from a manual tool into a collaborative workspace.
Combined with Cowork for file system operations and Claude in Chrome for browser-based research, Anthropic is building a complete workspace agent. For document management professionals, this means the AI does not replace your tools. It operates alongside them, handling the repetitive parts while you focus on the decisions that require judgment.
What This Means for Document Management
This is where the practical value lives. Opus 4.6 does not change what document management is. It changes how efficiently you can do it — if you bring the right expertise.
Migration Planning and Execution
Every data migration starts with the same problem: understanding what you have, where it needs to go, and what will break along the way. Source inventories. Metadata mappings. Content type transformations. Permission structures that need to be rebuilt. Exception rules for edge cases.
Traditionally, this analysis happens in stages. You inventory one site collection, map its metadata, document exceptions, then move to the next. With a million-token context window, a model can hold the entire scope simultaneously. Upload the complete source inventory, the target information architecture, and the migration rules, and the model can identify conflicts, flag unmapped content types, and draft transformation rules across the full dataset.
This does not eliminate the need for a migration specialist. It means the specialist spends less time on inventory and mapping mechanics and more time on the decisions that actually matter: which content structures to preserve, which to consolidate, and how to handle the hundreds of small exceptions that break automated migrations.
At Strator, we have run data migrations for some of Denmark's largest organizations across pharmaceuticals, finance, and healthcare. The pattern is always the same: 80% of the work is systematic and repeatable, 20% requires human judgment shaped by years of experience with specific platforms, regulatory requirements, and organizational politics. AI agents handle the 80% faster. The 20% is where consultants earn their value.
Compliance and Governance
Regulated industries — pharmaceuticals under GxP and EMA requirements, finance under DORA and MiFID II, healthcare under patient data regulations — need continuous verification that their document management meets requirements. Retention policies, sensitivity labels, access permissions, and audit trails all require regular review.
Agent teams that work in parallel can scan document libraries, verify retention labels against policy, flag permission anomalies, and generate exception reports. Tasks that take a compliance team days to perform manually can be drafted in hours.
But here is the critical distinction: the AI generates findings. A qualified professional validates them. In regulated environments, the signature on a compliance report carries legal weight. The AI cannot sign. A GxP-trained document management specialist can, because they understand not just what the label says but why it was applied, what regulatory context drove that decision, and what consequences follow from changing it.
This is where the human knowledge layer becomes essential. An AI agent can tell you that 47 documents in a validation folder have incorrect retention labels. It takes a regulatory specialist to determine whether those documents are superseded validation protocols that should have been archived, active records that were mislabeled during migration, or legacy content that predates the current retention policy entirely. Each scenario requires a different remediation path, and choosing wrong has audit consequences.
Daily Operations and Content Processing
Beyond large projects, Opus 4.6 improves day-to-day document operations. The combination of large context and substantial output means practical tasks become faster.
Summarizing meeting series into decision logs. Extracting action items from project correspondence. Classifying incoming documents against an information architecture. Generating metadata suggestions for content that was uploaded without proper tagging. Drafting standard operating procedures from existing process descriptions.
None of these tasks are new. Document management professionals do them every week. The difference is that an AI agent can handle the first draft, and a professional can review, adjust, and approve it. The review takes minutes instead of the hours the drafting would have taken.
The Collaboration Model
The most productive way to think about Opus 4.6 is not as a replacement for expertise but as an amplifier of it. A junior consultant with AI assistance can produce first-draft deliverables at a speed that previously required senior-level efficiency. A senior consultant can focus their time on the judgment calls, client relationships, and strategic decisions that AI cannot replicate.
At Strator, we see this in practice. Our consultants carry deep knowledge of SharePoint, regulated industries, and enterprise information management built over years of implementation work. That knowledge does not become less valuable when AI gets better. It becomes more valuable, because the bottleneck shifts from "can we process this data fast enough" to "do we understand what this data means in context."
AI provides speed. Human expertise provides direction. The combination is where real efficiency gains happen.
The Digital Sovereignty Dimension
There is one important consideration that European organizations should keep in mind.
Opus 4.6 introduces US data residency as an option, at a 10% price premium. However, European data residency is not currently available. Every prompt, every document processed by Claude, every agent team coordinating across your files is processed on US infrastructure.
For most document management tasks — working with public content, internal process documents, or non-sensitive operational data — this is perfectly workable. But for organizations subject to GDPR, NIS2, or DORA processing personal data, health records, or regulated content, the data residency question needs a clear answer before deployment.
Practical Recommendations
Classify before you connect. Before granting any AI agent access to document libraries, classify the content by sensitivity. Public and internal-use documents are generally fine. Confidential, personal, or regulated data requires assessment — and may require on-premises or EU-hosted alternatives.
Understand what EU hosting solves and what it does not. Anthropic may eventually offer European data residency. For many organizations, that could be sufficient — provided they classify their content carefully and manage what the AI is allowed to access. If your data is not subject to strict regulatory controls, EU-hosted infrastructure combined with proper access governance is a reasonable path forward.
However, for regulated industries where data must never leave the organization's domain, tenant, or control — pharmaceuticals under GxP, finance under DORA, healthcare under patient data regulations — the issue is not where the servers are. As long as Anthropic is a US-incorporated, US-controlled company, it remains subject to US legal frameworks including FISA Section 702, the CLOUD Act, and related provisions. These grant US authorities the ability to compel access to data regardless of where it is physically stored. EU hosting on US-controlled infrastructure does not resolve this. The capability is impressive. The jurisdictional reality makes it incompatible with European regulatory obligations for controlled data.
Consider a DPIA regardless. Even for non-sensitive use cases, deploying Cowork or API-based agent teams for document processing likely triggers a Data Protection Impact Assessment under GDPR Article 35. Conduct it proactively. It will force the right conversations about what data goes where — and that clarity benefits the organization whether or not AI agents are involved.
If you need help assessing your document management strategy, particularly in regulated environments where compliance and data sovereignty matter, Strator has the experience to guide that conversation. We work with Denmark's largest organizations across pharmaceuticals, finance, and healthcare, and we understand both the technology and the regulatory landscape.
Pricing
Opus 4.6 maintains the same API pricing as its predecessor: $5 per million input tokens and $25 per million output tokens. Processing the full one-million-token context window costs $5. Generating a full 128K token output costs approximately $3.20.
For consumer access through claude.ai, Opus 4.6 is available on Pro ($20/month), Max ($100–200/month), Team, and Enterprise plans. Cowork is available on all paid plans.
