GoSearch is an AI-driven enterprise search platform that unifies company knowledge across apps, providing real-time answers, summaries, and actionable insights using agentic AI.

Who is GoSearch designed for?

GoSearch serves both individuals and enterprise teams, including Engineering, IT, HR, Product, Marketing, Sales, GTM teams, and more, helping them discover insights, automate workflows, and make data-driven decisions.

What are GoSearch AI Agents?

AI Agents are no-code workflows that automate tasks and provide answers across connected tools and data sources, helping teams work faster and smarter.

How quickly can I start using GoSearch?

Teams and individuals can deploy GoSearch in hours to days, depending on the number of connected data sources and users.

What is GoSearch Free and who is it for?

GoSearch Free is a forever-free plan that connects personal apps (Gmail, Drive, Slack, Teams, etc.) for unified search across emails, docs, chats, and calendar. Ideal for individuals and small teams.

What is the difference between GoSearch Free and paid/enterprise plans?

Paid plans unlock broader integrations, team support, governance controls, and enhanced AI capabilities, while the free plan focuses on personal or small-scale use.

How does GoSearch pricing scale with users or data volume?

Enterprise pricing is typically usage-based or per-seat, scaling with the number of users, connected apps, and data volume.

Which data sources can GoSearch connect to?

GoSearch integrates with 100+ apps, including Slack, Gmail, Google Drive, Notion, Jira, Salesforce, and more.

Can GoSearch handle unstructured data like chats, tickets, and attachments?

Yes. Using AI-driven semantic search, GoSearch can interpret unstructured content to surface relevant results.

Can I add custom or internal data sources?

Yes. GoSearch supports custom connectors and integrations for enterprise systems, databases, and private repositories.

How quickly can new data sources be onboarded?

Many connectors can be added in hours, with minimal configuration, depending on access permissions.

What is federated search versus indexed enterprise search?

Federated search queries multiple live data sources directly; indexed search builds a consolidated searchable index.

What is a hybrid search architecture?

A hybrid approach indexes safe/static data while federating sensitive or real-time data, balancing speed, freshness, and governance.

When should I use federated, indexed, or hybrid search?

Federated: highly sensitive or dynamic data. Indexed: static, shared data needing fast results. Hybrid: most enterprise use cases.

What is Retrieval Augmented Generation (RAG)?

RAG combines retrieval of relevant documents with generative AI to produce coherent, summarized, context-aware answers.

Can RAG work with sensitive or regulated data?

Yes. In federated or hybrid models, RAG retrieves real-time data without duplicating it, maintaining privacy and compliance.

What AI models does GoSearch support?

GoSearch allows users to select from multiple large language models (LLMs) and customize AI workflows.

What are no-code AI Agents?

No-code Agents automate workflows, summarize data, or generate answers across apps without coding expertise.

Does GoSearch support summarization and insights extraction?

Yes. GoSearch can summarize documents, conversations, and tickets, and generate actionable insights for teams.

How does GoSearch handle security?

GoSearch supports role-based access, encryption, SSO/SAML, BYOC deployments, and zero-copy search to prevent data duplication.

How is user permission enforced?

Search results only show content the user is authorized to access. Permission checks are applied in real-time.

Does GoSearch comply with privacy regulations?

GoSearch is designed to meet enterprise compliance requirements, including GDPR, HIPAA, and other data governance standards.

Can GoSearch be deployed in a private cloud or VPC?

Yes. GoSearch supports enterprise deployment options for enhanced data control and compliance.

What makes GoSearch different from Glean or other enterprise search tools?

GoSearch offers lower TCO, hybrid search architecture, flexible AI workflows, real-time retrieval, broader integrations, and faster deployment.

Which other platforms are commonly evaluated as alternatives?

Common alternatives include Glean, Coveo, Lucidworks, Elastic Enterprise Search, Algolia, and Unleash.

Why might teams switch from Glean to GoSearch?

Teams often switch for lower cost, faster deployment, more AI customization, broader integrations, and stronger governance.

How does GoSearch compare to Unleash?

GoSearch offers self-serve AI agents, zero-copy real-time search, broader connectors, and transparent pricing, whereas Unleash often requires sales contact and indexed data.

Does GoSearch provide usage analytics?

Yes. Teams can see search trends, content gaps, and usage statistics to improve knowledge management.

Can GoSearch track which documents or sources are most accessed?

Yes. This helps identify valuable knowledge assets and optimize content strategy.

Can GoSearch search large attachments or multimedia files?

Yes, GoSearch can parse PDFs and text-based attachments, and videos. It can also search by image.

What are common trade-offs between federated vs indexed search?

Federated search is real-time and privacy-safe but can have latency. Indexed search is faster but may duplicate sensitive data. Hybrid often balances both.

Are there any limits on the number of connected apps or users?

Limits depend on the plan: Free accounts have personal usage limits; enterprise plans scale to hundreds or thousands of users.

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AI Innovators: Rebecca Yang

Building AI Platforms, Agents, and the Future of Engineering

Rebecca Yang, Director of Engineering at HubSpot, featured in the GoSearch AI Innovators series, discusses AI platforms and the role of context and MCP in enterprise AI deployments.

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About this episode

AI INNOVATOR

Rebecca Yang, Director of Engineering | HubSpot

Rebecca Yang is Director of Engineering at HubSpot, where she leads engineering initiatives across AI-powered data systems, smart properties, intent signals, and platform infrastructure. She previously helped scale Clearbit before its HubSpot acquisition.

In this edition of AI Innovators, we sat down with Rebecca Yang, Director of Engineering at HubSpot, to explore AI infrastructure, platform thinking, MCP, enterprise adoption, and what separates real AI innovation from hype. Having built AI-powered data systems inside one of the largest go-to-market platforms, Rebecca shares why context is the enterprise moat, how to tell a platform from a feature, and what governance enterprise AI needs before it can earn trust.

Key Takeaways:

Context is the enterprise moat: AI value depends on how well systems connect internal and external data — as you learn the moment a connector breaks.
Platforms outlast features: Real AI platforms hold up when underlying models change; features break when models are swapped.
Agents aren't workflows: Most "agents" today are workflows with LLM calls embedded inside. True autonomy means independent decisions — and a far larger blast radius when something goes wrong.
Governance earns trust: The real enterprise AI risk isn't a bad chatbot reply — it's silent, large-scale data corruption. Provenance, reversibility, and guardrails are non-negotiable.
Execution beats model selection: Successful rollouts share clear accountability, strong measurement, and deep enablement — backed by real leadership buy-in.

Read the full conversation with Rebecca Yang to learn how AI platforms, agents, and Model Context Protocol are reshaping enterprise engineering — and why context and governance separate lasting AI from hype. Subscribe to AI Innovators for monthly insights straight to your inbox.

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