Gaia is Cohesity’s generative-AI conversational search assistant — ask your own data questions in plain English and get cited answers — turning the vast backup data you already hold (normally inert) into a searchable knowledge asset. Grounded, cited, secure.
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This page covers Gaia — AI insight over your data. The rest of the Cohesity portfolio:
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A generative-AI conversational search assistant — ask your own data questions in plain English, get cited answers — turning the backup data you already hold into a searchable knowledge asset.
What consolidation actually replaces, dimension by dimension.
| Dimension | Unprotected / signature email | Gaia (Cohesity) |
|---|---|---|
| Backup data | Inert (cost only) | Searchable knowledge asset |
| Finding info | Manual, keyword search | Ask in plain English |
| Answers | A list of hits | Synthesised, cited answers |
| AI trust | Hallucination risk | Grounded (RAG) + cited |
| Security | Leak risk with naive AI | Access-aware, controlled |
| Reach | One silo | Backup, on-prem, Databricks/Fabric, M365 |
| Data value | Just stored | Protect, secure AND get insight |
| Positioning | Late me-too | Pioneer (2024), advancing |
Gaia turns your inert backup data into a searchable knowledge asset — ask in plain English, get grounded, cited, secure answers (RAG). It’s the AI-insight layer of the Cohesity platform (protect + secure + insight), not a general enterprise-search replacement. TechBag sets the right expectations.
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Uses the years of documents, records, files and application data you already back up as the searchable source, turning an inert corpus into a knowledge asset.
Ask natural-language questions and get AI answers grounded in your own data through retrieval-augmented generation (RAG), not keyword searches.
Answers are grounded in your data and cite their sources, so they are relevant, checkable and less prone to the hallucination of ungrounded AI.
Gaia respects security and access controls and works over data you already hold, your backups, so insight doesn’t expose sensitive data.
Reaches beyond backup: on-premises backup data, a Gaia Catalog spanning Databricks and Microsoft Fabric, and Microsoft 365 Copilot integration.
All workloads share one recovery plane; the goal is clean, rapid restoration, not backup.
Gaia lets you ask your own data questions in plain English and get cited answers — turning inert backup data into a knowledge asset — the AI insight of the Cohesity portfolio.
Ask in plain English, such as ‘Summarise our agreements with Y’ or ‘Find records about Z’, with no query language needed.
Uses RAG: it retrieves relevant content from your data, then generates an answer grounded in it rather than in the model’s training.
Summarises documents, synthesises across many sources and extracts key points, giving concise answers rather than search hits.
Searches and reasons over the backup data you already hold, turning an inert corpus into a searchable knowledge source.
Every answer cites its sources in your data, so you can verify it and trace it back instead of trusting an unsourced claim.
Grounding answers in your data through RAG reduces the hallucination risk of ungrounded generative AI.
Respects security and access controls, so people only get answers from data they are allowed to see.
Built for controlled enterprise use: grounded in your data and working over data you already hold, without external exposure.
Extends to on-premises backup data on platforms such as Cisco UCS, HPE and Nutanix, not just cloud, for hybrid estates.
A Gaia Catalog enables discovery across broader sources, including Databricks and Microsoft Fabric, beyond backup data.
Integrates with Microsoft 365 Copilot, bringing Cohesity-protected data into the tool where people already work.
Announced in early 2024, Gaia was among the first generative-AI conversational search assistants for enterprise backup data.
The overview, getting started, and the core workflows.
Gaia conversational AI.
Conversational search on your data.
The broader Cohesity platform.
Want a live, India-context walkthrough for your environment?
Book a guided demo →Here’s what genuinely sets Cohesity Gaia apart.
Your backups hold years of documents, records, emails and application data, yet they sit unused unless you restore. Gaia lets you ask that data questions in plain language and get summarised answers that cite your own content, so an insurance cost becomes a usable knowledge source.
Naive generative AI over enterprise data can invent answers, can’t be verified, and can surface data to the wrong people. Gaia grounds answers in your data through RAG, cites the sources so you can check them, and respects access controls, so people only get answers from data they may see.
Cohesity announced Gaia in early 2024, among the first conversational AI assistants for enterprise backup data, and has since added on-premises data, a Gaia Catalog and Microsoft 365 Copilot integration. It runs where your backups already live, on a platform protecting 12,000+ customers.
AI over data is only as useful as the data it reaches. Gaia now covers on-premises backup data (Cisco UCS, HPE, Nutanix), wider sources such as Databricks and Microsoft Fabric through the Gaia Catalog, and brings Cohesity-protected data into Microsoft 365 Copilot.
Gaia is part of Cohesity’s platform, which protects your data (DataProtect, NetBackup), secures it (threat detection, FortKnox vaulting) and, with Gaia, yields insight from it. The data is already there, so there is no separate pipeline to build, and the platform’s access controls carry over.
Gaia lets you question the data Cohesity already protects in plain English and get cited answers. It is most valuable as part of the Cohesity platform. Rubrik and others are adding AI features too, and Gaia is not a general enterprise-search or knowledge-management replacement.
Map what you back up, your use cases (search, compliance, discovery) and your Cohesity estate. TechBag sets expectations.
Enable Gaia over your Cohesity-protected data with access controls applied, and start asking questions in plain English.
Extend Gaia to on-prem data, to Databricks and Fabric via the Gaia Catalog, and into M365 Copilot, so insight spans your estate.
Build Gaia into compliance, discovery and knowledge workflows. TechBag models it in INR/GST and supports you locally.
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
“We ask questions in plain English and get cited answers from years of our own backup data. It turned a cost into an asset.”
“Grounded, cited and access-aware: fewer hallucinations, answers we can verify, no leaks. That made AI over our data adoptable.”
“Cohesity already protects our data, so Gaia had it ready. We didn’t need to build a separate data pipeline.”
“Searching years of records conversationally for compliance and discovery saved us enormous time over manual searching.”
“With on-prem data, Databricks and Fabric via the Gaia Catalog, and M365 Copilot, we get insight across our estate, not one silo.”
“It’s an insight layer on our Cohesity platform. TechBag was clear it isn’t a standalone enterprise-search replacement.”
“Cohesity announced Gaia in 2024 and keeps advancing it, which gave us confidence it’s a serious capability.”
“One platform protects our data, secures it and gives us AI insight from it. TechBag scoped it in INR/GST.”
Analyst firms bury this view behind paywalls, and review-site grids score satisfaction, not fit for your estate. So here’s TechBag’s synthesis of the AI-over-enterprise-data / gen-AI search market — tap any vendor to see why it sits where it does.
Execution strength vs product vision — the classic market map, minus the paywall.
Gen-AI search over your backup/enterprise data (pioneer). This page's product.
The grid nobody publishes — AI answer quality vs insight depth & integration.
Over your data, responsibly, integrated.
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Rubrik AI, general enterprise search, DIY RAG and M365 Copilot — honest lanes; the edge is responsible gen-AI over the data you ALREADY back up (grounded, cited, secure), integrated with data protection. Rubrik shop? Rubrik AI. M365-only? Copilot (Gaia integrates). We say so.
| Dimension | Cohesity Gaia | Rubrik AI | Generic enterprise search | DIY RAG (build it) | M365 Copilot (alone) | No AI over data |
|---|---|---|---|---|---|---|
| Position | Gen-AI search over your backup/enterprise data (pioneer) | Rival DP vendor adding AI | Keyword/enterprise search (not gen-AI over backup) | Build your own RAG (effort) | MS AI over M365 content | Backup data stays inert |
| Conversational (natural language) | Yes — plain English | Yes (AI) | Mostly keyword | If you build it | Yes | No |
| Over your BACKUP data (comprehensive corpus) | Yes — data's already there | Some (its platform) | Not backup-focused | You'd wire it up | M365 content only | No |
| Grounded + cited (reduced hallucination) | Yes — RAG + citations | Yes | Search results (not synthesised) | Depends on your build | Yes (grounded in M365) | N/A |
| Security / access-aware | Yes — respects controls | Yes | Varies | Your responsibility | Yes (M365) | N/A |
| Reach (on-prem, broader sources) | Backup, on-prem, Databricks/Fabric, M365 Copilot | Its platform | Configured sources | Whatever you wire | M365 only | None |
| Integrated with data protection | Yes — on Cohesity platform | On Rubrik platform | Separate | Separate build | Separate | N/A |
| Effort to get value | Low (data's there, it's built) | Low (on its platform) | Deploy/configure | High (build RAG) | Low (if on M365) | None (but no value) |
| Best fit | AI insight over the data Cohesity already protects (esp. Cohesity customers) | AI on the Rubrik platform | General enterprise search | Custom RAG (have the team) | AI over M365 content | Nobody — leaves backup data inert |
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Drag the sliders (count knowledge workers; hours spent finding info as loaded cost). Estimates contrast inert backup data (manual searching, dormant knowledge) vs Gaia (conversational, cited answers across years of data) — the win is time saved finding information and value unlocked from data you already hold. Illustrative; Gaia is quote-priced (part of the platform).
Loaded cost = salary + overheads per productive hour. Illustrative only — your TechBag quote models your actual environment and modules.
Cohesity Gaia is quote-priced as part of the Cohesity platform — an AI-insight capability over the data Cohesity protects, scoped to your deployment. It adds insight to your data-protection investment (data’s already there). TechBag scopes it, sets expectations, and quotes in INR/GST.
Best for unlocking your protected data
Best for a broader rollout
Best for protect + secure + insight
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Tell us your requirements and current tools — we’ll model it against what you spend today.
Take this into your next vendor call — including ours.
How would Gaia let us ask our stored backup data questions in plain English and get cited answers?
How does Gaia ground its answers (RAG), cite sources and respect access controls over our data?
Does Gaia need Cohesity to protect our data first, and what does it add on top of our data protection?
Can Gaia’s conversational search serve our compliance, discovery and knowledge needs across years of data?
Need insight across on-prem and broader sources (Databricks/Fabric) and in M365 Copilot? Gaia's reach is broadening across your estate.
Where does Gaia stop as an insight layer, and which enterprise-search use cases does it not replace?
Rubrik shop? Rubrik AI. M365-only insight? Copilot. Custom needs + AI team? DIY RAG. TechBag compares honestly.
Quote-priced (enterprise — part of the Cohesity platform) — TechBag scopes it and quotes in INR/GST.
Scope Cohesity Gaia (ask your backup data questions in plain English, get cited answers, responsibly) — or let a TechBag advisor set the right expectations (the AI-insight layer of the Cohesity platform) and quote it in INR/GST.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.