Software advice
Best AI Enterprise Search Software in 2026
AI enterprise search software is a platform that indexes documents, tickets, wikis, mail and databases from many internal systems, respects each user's access rights, and returns ranked results or cited answers written by a language model. It differs from a website search box, which covers public pages, and from a general chatbot, which has no index of your sources. Large organizations use it so staff stop hunting across tools.
Quick answer
Dust ranks first because its seat prices, SOC 2 Type II claim and EU or US residency are printed. Algolia fits teams that build search themselves on printed usage rates. IntraFind fits buyers who want German hosting choices and ISO 27001 stated.
A buyer who needs one search across file shares, SharePoint, ticketing and a wiki usually faces two questions: who can see which result, and who runs the index. Vendors lead with agents and answer boxes, yet most pages say little on hosting, model training or price. We read vendor pages in November 2026 and ran no relevance test, so claims about answer quality belong to the vendors. This ranking therefore weighs what a buyer can check before a pilot: printed prices, stated certifications, deployment choices, connector counts and whether the page says customer content stays out of model training. Where a page was silent, we say so.
The 10 best AI enterprise search software in 2026, ranked
There is no score. Vendors can pay for more visibility on this website, for example a higher place in a ranking or more room on a page. Commercial relationships can also affect which products we feature and how prominently. How we rank.
| # | Tool | Best for | Free plan | Entry price |
|---|---|---|---|---|
| 1 | Dust | Teams of up to a few hundred wanting answers from Slack, Notion and Drive in one place | Yes | 24 euros per seat per month on Pro, billed yearly |
| 2 | Algolia | Developers who need a hosted search index with printed usage rates and a free tier | Yes | Free tier, then $0.50 per extra 1,000 search requests on Grow |
| 3 | IntraFind | German-speaking public bodies and companies wanting on-premises search with stated ISO 27001 | Trial | Quoted |
| 4 | Vectara | Product teams building retrieval-augmented answers who need SaaS, VPC or on-premises options at printed prices | Trial | $100K per year for one SaaS deployment |
| 5 | Ayfie | Nordic and EU organizations wanting assistants whose data stays in their own environment | No | Quoted |
| 6 | Intergator | Mid-size German organizations wanting an on-premises or private-cloud search with three clear editions | No | Quoted |
| 7 | Squirro | Banks and industrial groups wanting cited answers with an audit trail and an on-premises option | No | Quoted |
| 8 | Mindbreeze | Large enterprises with hundreds of source systems that need governed assistants on top of one index | No | Quoted |
| 9 | Zeta Alpha | R&D and engineering teams in manufacturing, chemistry or pharma with PLM, ERP and QMS silos | Trial | Quoted |
| 10 | Sinequa | Large organizations wanting context-engineered agents and a no-code assistant builder over many sources | No | Quoted |
- 1
Dust
Dust ranks first because a buyer can read nearly everything before talking to sales: seat prices for Free, Pro and Max, a SOC 2 Type II statement, and US or EU data residency. Its pages list 20 plus frontier models and connectors to common work tools. It reads more like an agent workspace than a classic index, and its pricing page does not say whether customer data trains models.
Strong on
- Seat prices printed from 24 euros a month, with a Free plan for trying it
- SOC 2 Type II stated, plus US or EU data residency on Business and Enterprise
- Enterprise adds single-tenant deployment and unlimited connectors and MCP servers
Weak on
- Credits are used up faster by stronger models and do not roll over
- Pricing page does not say whether customer content is used for model training
Skip it if: Organizations that must index on-premises file servers with fine-grained legacy access rights and cannot use a hosted service. Pro includes 8,000 credits per seat each month, and unused credits do not roll over. Enterprise is quoted.
- 2
Algolia ranks second because its pricing page prints request and record rates, a free tier with 10,000 requests and 50,000 records, and hosting in the US, UK and EU West. AI features such as NeuralSearch sit in Elevate. It is a search service for builders, not a finished internal search with connectors to mail and file shares, and its page names no certifications.
Strong on
- Free tier needs no credit card and includes 10,000 search requests a month
- Per-request and per-record overage rates are printed for Grow and Grow Plus
- Pricing page states hosting in the US, UK and EU West on lower plans
Weak on
- No ready-made connectors to internal systems appear on the pricing page
- NeuralSearch and personalization sit in the quoted Elevate tier
Skip it if: Knowledge teams without developers who want to point a tool at SharePoint and mail and have it work. Records cost $0.40 per extra 1,000. Grow Plus adds AI ranking at $1.75 per 1,000 requests.
- 3
IntraFind
IntraFind ranks third because its page states the most about governance: ISO/IEC 27001 certification, GDPR and EU AI Act claims, no model training, and deployment on-premises, in a sovereign cloud or as a managed service. It connects to more than 80 sources and offers a trial. The cost is a missing price and a vendor project to get started.
Strong on
- States ISO/IEC 27001 certification and no model training on its platform page
- Search, chat and agents inherit each user's access rights from the source
- Offers on-premises, sovereign cloud or managed service, plus a free trial
Weak on
- No price or plan structure is printed, so budgeting needs a quote
- Connector list of more than 80 sources is smaller than the largest platforms
Skip it if: Startups wanting to sign up with a card and run a team search by the afternoon. No price is printed. A free trial is offered, and licensing for iFinder, iAssistant and iHub is quoted.
- 4
Vectara
Vectara ranks fourth because it prints starting prices for three deployment models, offers a 30-day all-feature trial and lets you bring ChatGPT, Claude or Gemini. Those prices set a high floor, and the pricing page named no certifications, regions or usage limits. It is a retrieval platform for builders, not a ready-made search page for staff.
Strong on
- Starting prices are printed for SaaS, VPC and on-premises deployments
- Bring-your-own-model option supports ChatGPT, Claude and Gemini as generators
- Written uptime and support-response SLAs are offered at the Enterprise tier
Weak on
- Entry price of $100K a year is out of reach for small teams
- Pricing page lists no certifications, regions or capacity limits
Skip it if: Departments with a budget under six figures or no engineers to build the application layer. VPC starts at $250K and on-premises at $500K a year. A 30-day trial includes all features.
- 5
Ayfie
Ayfie ranks fifth because its page makes concrete data claims: nothing leaves your environment, nothing trains the models, and one agent processes everything in Norway. It lets you pick GPT, Claude or Gemini and cites sources in replies. No certification is named, only an architectural GDPR claim, and no price appeared on the page we read.
Strong on
- States that nothing is used to train the models
- Replies link to the source facts, and model choice includes GPT, Claude and Gemini
- Ayfie Make builds workflows visually or extends them with code
Weak on
- No named certification, only a GDPR compliance claim
- No price or plan limits on the home page
Skip it if: Buyers who need a printed certification list or a public price before opening a conversation. The home page prints no figures and links to a separate pricing page that was not read here.
- 6
Intergator
Intergator ranks sixth because it sells three editions in plain terms: Core for keyword search, AI for semantic search and AI+ with a language model. It runs on-premises or in a private cloud, claims GDPR conformity and adds Agentic Chat in version 6.8. The page names no ISO certification, lists source types instead of connectors and prints no price.
Strong on
- Three editions (Core, AI, AI+) let a buyer start with keyword search only
- Deployment is on-premises or private cloud, with content kept in the organization
- Microsoft Teams plugin and answers with sources are listed
Weak on
- Connectors are described as source types, with no count on the home page
- No named certification beyond a GDPR conformity claim
Skip it if: Global companies needing hundreds of prebuilt connectors or a vendor with a large US presence. No price is printed. Buyers request a demo or use the vendor's product selection tool to pick an edition.
- 7
Squirro
Squirro ranks seventh because its page shows named results, such as 3,300 semantic search users at Henkel and an eight-week path to live users, and offers on-premises enterprise AI with a Trust Center on a third-party platform. It also provides guardrails, a privacy layer and a regulatory document agent. It names no certification on the home page and gives no pricing.
Strong on
- States eight weeks from signed agreement to live users
- Offers on-premises enterprise AI and a Trust Center hosted on Drata
- Agents for regulatory search and RFP drafting include human review and audit trail
Weak on
- No certification is named on the home page
- Pricing and cloud hosting regions are not stated on the page
Skip it if: Small teams wanting self-serve signup, since the route in is a demo and a scoped project. No price is printed. The site directs visitors to book a demo, and hands-on demos need no sign-up.
- 8
Mindbreeze
Mindbreeze ranks eighth because it cites more than 500 connected data sources, an IDC MarketScape leader placement and an MCP server, but the home page states no hosting options, certifications or price. Its Insight Workplace layer adds pre-built agents and journeys. It suits large estates, and a smaller buyer has less to verify before a demo.
Strong on
- Page cites more than 500 connected data sources
- Insight Touchpoints offer pre-built governed agents, and an MCP server is listed
- Named a leader in the IDC MarketScape for knowledge discovery software, 2025
Weak on
- Home page names no hosting options and lists no specific certifications
- No price or plan structure is published on the site
Skip it if: Teams under a few hundred people wanting a tool they can price and trial alone. The site prints no pricing. Mindbreeze InSpire and Insight Workplace are scoped through a sales conversation.
- 9
Zeta Alpha ranks ninth because it is built for industrial knowledge, with agentic search, deep research and an MCP server, and runs in the cloud or on-premises. That focus helps R&D buyers and narrows the audience. The home page names no certifications, no connector list and no price, so a broader buyer has less to compare.
Strong on
- Runs in the cloud or on-premises as one platform for RAG and agents
- Targets PLM, ERP and QMS silos with end-to-end permission management
- Offers a configurable LLM ingestion pipeline and an MCP server
Weak on
- No certifications or connector list on the home page
- Pricing is on a separate page, so the home page gives no cost
Skip it if: General office teams searching mail and shared drives, since the product speaks to R&D and manufacturing. The home page prints no price. A trial request is offered and pricing details sit on a separate page.
- 10
Sinequa
Sinequa ranks last because its site now sits inside the Argonos platform of ChapsVision, the product pages state over 200 connectors and an assistant builder, and the trust page we opened showed no content. No hosting detail, certification or price appeared. It may be strong in practice, but a buyer has little to verify beforehand.
Strong on
- Over 200 connectors and a no-code assistant builder are stated
- Lets buyers choose AI model, deployment and configuration
- Listed as a Representative Vendor in the Gartner Market Guide for Enterprise AI Search
Weak on
- Trust center page returned no certification or hosting detail when opened
- Ownership by ChapsVision and the Argonos rebrand add contract questions
Skip it if: Buyers who need hosting, certifications and prices confirmed from public pages before a first call. No pricing is shown. The site claims the lowest total cost of ownership without giving a figure.
How these AI enterprise search software were judged
How accurate are the answers from enterprise search software?
Answer quality depends on three things a vendor page rarely proves: how well connectors pull the right text, whether permissions are checked at query time, and whether each answer links to its source. Ayfie says each reply links to where the facts came from, and Squirro describes source-cited answers with an audit trail. IntraFind states that search, chatbots and agents only see what a user is authorized to see. None of these pages publishes a relevance score. Build a test set of fifty real questions from your staff, with known correct documents, and run every shortlisted vendor against it before signing.
What does enterprise search software cost?
Three pricing shapes appear. As of November 2026, Dust prints Pro at 24 euros per seat a month billed yearly and Max at 120 euros. Algolia prints a free tier with 10,000 search requests, then $0.50 per extra 1,000 on Grow. Vectara prints SaaS from $100K a year, VPC from $250K and on-premises from $500K. Mindbreeze, Sinequa, Squirro, Ayfie, Intergator, IntraFind and Zeta Alpha show no price on the pages we read. For quote-only vendors, ask what is counted: users, documents, queries or connectors, and whether the AI assistant is part of the base license.
Where does the search index live and is your content used for training?
An enterprise index holds copies of text from mail, contracts and HR files, so location and training matter before relevance. IntraFind lists on-premises, sovereign cloud or managed service, states ISO/IEC 27001 and says no model training. Ayfie states nothing is used to train its models. Dust lists US or EU residency and SOC 2 Type II but its pricing page does not address training. Vectara and Algolia pages did not state a certification, so the vendor's policy was not checked beyond those pages. Ask for a written statement on training, sub-processors and deletion of an index at exit.
How hard is it to switch enterprise search vendors?
Your documents stay in their source systems, so the index itself is rebuilt rather than exported. The lock-in sits in connector configuration, relevance tuning, permission mappings and any agents or assistants built on the vendor's tools. Vectara's pricing page lets you bring your own model, and Ayfie lets you switch between GPT, Claude and Gemini, which reduces model lock-in. Several vendors now list an MCP server, including Mindbreeze, Sinequa and Zeta Alpha, which lets other agents query the index. Before signing, ask how long a re-index of your volume takes and who owns the tuning rules.
Which enterprise search platform fits your company size and sector?
Start from who must build and who must govern. A team of a hundred that wants answers inside Slack fits Dust, which lists Business plans for teams up to 100 people. An engineering group embedding search in a product fits Algolia or Vectara. A public body or bank that keeps data on its own servers fits IntraFind, Intergator, Ayfie or Squirro. A manufacturer or lab with PLM and QMS silos fits Zeta Alpha, and a multinational with hundreds of sources fits Mindbreeze or Sinequa. European buyers should confirm the contracting entity as well as the hosting region.
How to choose an AI enterprise search platform in three steps
- Write the permission rules before the demo. List ten users with different access, such as an HR partner, a contractor and a board assistant, and the documents each must never see. Ask every vendor to show a query run as each person on your own sample sources. Check whether permissions are read live from the source or copied into the index on a schedule, because a copy can lag behind a revoked right. IntraFind and Dust both describe permission models, but only a live demonstration on your data shows how they behave when rights change.
- Run a fifty-question test on your own documents. Collect real questions from three departments, each with the document that holds the answer. Load a representative slice of sources into two or three shortlisted products and score each one on whether the right document appears first, whether the written answer is correct and whether the citation opens the right passage. Record queries that return nothing. Squirro's eight-week deployment claim and Vectara's 30-day trial give you windows to plan this, but the test set should be yours, not the vendor's.
- Fix deployment, term and exit terms in writing. Decide whether SaaS, a private cloud or your own servers is acceptable, then collect the same items from each vendor: annual cost at your user and document count, AI assistant add-ons, support hours, uptime commitments and the exit process. Vectara shows how far apart deployment prices can be, from $100K for SaaS to $500K on-premises. Ask what happens to the index and to logs of user questions after termination, and request a deletion confirmation within a stated number of days.
Frequently asked questions
What is the best AI enterprise search software in 2026?
Dust ranks first here because it prints seat prices from 24 euros a month, states SOC 2 Type II and offers EU or US data residency. Algolia is the better pick for developers who want a free tier and printed request rates, and IntraFind suits buyers who want on-premises or sovereign hosting with ISO 27001 stated.
Is enterprise search the same as an AI assistant like Copilot or ChatGPT?
No. An assistant answers from a model and whatever you paste in, while enterprise search keeps a permission-aware index of your systems and retrieves from it. Many platforms here, including Dust, Ayfie and IntraFind, combine both, so check whether an answer cites the document it came from and honors who may see it.
Can enterprise search run fully on-premises?
Yes, with some vendors. IntraFind lists on-premises, sovereign cloud or managed service. Intergator names on-premises and private cloud, Vectara prices an on-premises deployment from $500K a year, and Squirro links an on-premises offer. Mindbreeze, Sinequa and Dust pages did not state a self-hosting option, apart from Dust listing single-tenant deployment for Enterprise.
Does enterprise search send our documents to OpenAI or Anthropic?
It can, depending on the model you choose. Dust lists models from OpenAI, Anthropic, Google and Mistral, and Ayfie lets you pick GPT, Claude or Gemini. Ayfie says nothing leaves your environment, and IntraFind says no model training. Ask each vendor which provider receives text, in which region, and under what retention terms.
How long does it take to roll out enterprise search?
It ranges from minutes to months. A Dust or Algolia account can be opened without a sales call, and Vectara offers a 30-day trial. Squirro states eight weeks from signed agreement to live users. Large connected platforms such as Mindbreeze and Sinequa scope projects with vendor teams, so plan for a pilot before a full rollout.
Is there a free enterprise search tool with AI?
Partly. Dust lists a Free plan with 500 lifetime credits, and Algolia lists a free tier with 10,000 search requests and 50,000 records a month. Vectara offers a 30-day trial with all features, and IntraFind offers a free trial. Quote-only vendors such as Mindbreeze and Squirro direct buyers to demos.
How many connectors does an enterprise search product need?
Count your own sources, not the vendor's total. Mindbreeze cites more than 500 connected data sources, Sinequa says over 200 connectors, IntraFind lists more than 80 data sources and Dust lists 70 plus connectors on its home page. A long list matters less than whether your two or three core systems sync permissions correctly.
What is the difference between enterprise search and a knowledge base tool?
A knowledge base tool holds articles written inside it, while enterprise search reads from many systems where content already lives. A wiki with AI search covers only its own pages. If staff keep files in SharePoint, tickets in Jira and chats in Slack, an enterprise index across all three is the better fit.