47 things to evaluate before you commit to an AI workspace — covering multi-model chat, AI agents, IT governance, security, integrations, pricing, and everything your security team will ask about.
Most companies evaluating an AI workspace make the same mistake: they test the chat interface, decide it feels good, and buy. Six months later, IT is fielding a security incident, the budget team has no idea what AI is costing, and engineers are still copy-pasting between Salesforce and a chat window.
An AI workspace isn't a productivity app. It's infrastructure. And infrastructure requires a proper evaluation.
This checklist covers every dimension a serious enterprise evaluation should include — from multi-model AI chat to AI agents, IT governance, security, integrations, and total cost of ownership. Work through it with your procurement team, your CISO, and whoever will own AI deployment.
We've organized this checklist into seven categories. Tick the boxes as you evaluate. By the end, you'll have a clear picture of where any platform stands — and where it falls short.
Every AI workspace starts with chat. But not all AI chat experiences are equal. The difference between a single-model chat tool and a true multi-model AI workspace is significant — both in capability and in cost.
The right AI workspace for enterprise should give employees access to the best model for any task, not lock them into one vendor's model. A coding task runs better on Claude. A summarization task might run faster on Gemini Flash. A reasoning-heavy analysis might warrant GPT-4o. Smart routing means employees don't have to think about this — the platform handles it automatically.
☐ Multi-model access - Access to GPT-4o, Claude, Gemini, Llama, Mistral, DeepSeek — not just one provider's models.
☐ Smart model routing - Automatic routing to the optimal model per task type, without manual selection.
☐ Model switching mid-conversation - Ability to change models within an active chat without starting over.
☐ File upload and analysis - Upload PDFs, spreadsheets, images, and code files. RAG for large documents.
☐ Web search with citations - Real-time search with clickable source links, not just static training data.
☐ Shared prompt library - Team-wide prompt templates so best practices are reusable, not locked in one person's head.
☐ Image generation - Native image generation (DALL-E, Flux, or equivalent) within the workspace.
☐ Conversation history and search - Persistent, searchable chat history — not just within a session.
☐ Chat export - Export conversations as PDF or Markdown for documentation or compliance purposes.
Chat is where employees start. Agents are where the real value is.
The distinction matters. An AI chat tool gives someone a faster way to write an email. An AI agent in your CRM can pull account history, surface objections from the last three calls, draft a deal summary, and update the opportunity stage — without the rep ever leaving Salesforce.
When evaluating an AI workspace, ask whether it offers named, deployable AI agents with domain expertise — not just a chat interface with a system prompt. The architecture is completely different, and so are the outcomes.
☐ Named, deployable agents - Agents with identities, roles, and configurations — not just chat with a custom system prompt.
☐ No-code agent builder - Non-technical users can create and deploy agents in plain language — no engineering required for standard use cases.
☐ Pre-built agent templates - Ready-to-use agents for sales, support, HR, engineering, legal, and recruiting. Not starting from scratch every time.
☐ Event-triggered agent runs - Agents that activate on external events — a new Jira ticket, a Salesforce stage change, an incoming support email.
☐ Scheduled agent runs - Cron-based scheduling for recurring tasks: daily reports, weekly summaries, monthly reviews.
☐ Reusable skills / expertise packages - Packaged domain expertise that can be shared across multiple agents. Not rebuilding the same logic per agent.
☐ Agent sharing and publishing - Agents built by one team can be published for the whole company to use — with governance inherited automatically.
☐ Agent usage analytics - Usage frequency, which skills fired, which users, cost per agent. You need this to measure AI ROI.
Learn more about: Top 10 AI Agents for Customer Service Automation in 2026
AI agents are only as useful as the systems they can reach. The right AI workspace should integrate natively with the tools your teams already live in — not require you to build custom integrations for every connection.
Connector depth matters as much as breadth. A Salesforce connector that can only read data is fundamentally different from one that can read accounts, write opportunity notes, update stage, and pull reports. Ask for specifics.
☐ Salesforce (read/write) - Accounts, contacts, opportunities, cases. Not just read-only.
☐ Jira and Confluence - Issues, sprints, boards, pages, spaces. Create, update, transition.
☐ Google Workspace - Drive, Docs, Sheets, Calendar. Read and write, not just search.
☐ Slack and Microsoft Teams - Post messages, respond in threads, operate as a native bot in both.
☐ SharePoint and Notion - Document management for both Microsoft and Atlassian/Notion ecosystems.
☐ ServiceNow and SAP - Enterprise systems for ITSM and business operations. Important for mid-market and enterprise.
☐ GitHub - Repos, PRs, issues. Agents that can review code, draft comments, and create issues.
☐ Custom API support - Connect any REST API with auth. Essential for proprietary internal systems.
☐ - Per-agent connector permissions - Each agent has scoped read/write access — not blanket Salesforce access for every agent.
This is where most AI workspace evaluations break down. IT and security teams are handed a demo of the chat interface and asked to approve a platform. That's not how it should work.
Governance isn't a feature — it's the foundation. The right AI workspace ships governance by default, not as an enterprise add-on. Every team, from the free trial to the largest deployment, should have access to audit trails, PII redaction, and cost controls.
If a platform only offers governance controls at the highest tier, that's a red flag. Shadow AI exists precisely because lower-tier tools lack the controls that make IT comfortable with widespread deployment.
Learn more about: What Is AI Governance? And How Does an AI Governance Platform Work?
☐ Full audit trail - Every chat message and every agent action logged. Who used what, when, what model, what input and output.
☐ Agent-level audit trail - Specifically: "This agent accessed these Salesforce records for this user at 2:47pm." Not just chat-level logs.
☐ PII redaction - Auto-detection and redaction of PII before queries hit model providers. Configurable. Pre-model.
☐ Model availability controls - Admins can restrict which models are available to which teams. Not all teams need access to all models.
☐ Bring Your Own Key (BYOK) - Your data flows directly to model providers. The AI workspace vendor never sees your prompts or outputs.
☐ Per-team budget controls - Spending limits per team, per user, with alerts and hard caps. Not just a global monthly limit.
☐ Real-time cost analytics - Cost per team, per user, per model, per agent. Real-time — not a report at end of month.
☐ Content guardrails - Configurable content policies at the workspace level. Compliance-critical for regulated industries.
☐ Data retention controls - Admin-configurable retention policies. Required for GDPR, HIPAA, and most enterprise data governance.
☐ Data isolation between workspaces - Complete separation. No cross-contamination between company data and other tenants.
☐ No training on customer data - Contractual guarantee. Not just a policy statement — it must be in the contract.
☐ SOC 2 Type II certification - Not SOC 2 Type I. Type II covers a period of time, not a point-in-time assessment. Ask for the report.
☐ ISO 27001 certification - Required for many enterprise contracts, especially in financial services and healthcare.
☐ HIPAA / BAA availability - Business Associate Agreement available if you operate in healthcare or process health data.
☐ GDPR compliance - Data processing agreements, right to erasure, data residency options for EU companies.
☐ Encryption in transit and at rest - TLS 1.3 in transit. AES-256 at rest. Non-negotiable.
☐ SSO (SAML / OKTA / Azure AD) - Single sign-on for enterprise deployments. Required for any company with a mature identity stack.
☐ SCIM provisioning - Automated user provisioning and de-provisioning. Critical for large-scale deployments and offboarding.
☐ Web application - Full-featured web app. Table stakes, but verify it's not just a wrapper around a chat API.
☐ Slack bot (native) - Agents accessible as a Slack bot. Not a webhook workaround — a native, conversational Slack integration.
☐ Microsoft Teams bot (native) - Same as Slack, but for Teams-first organizations. Both matter — most enterprise orgs use one of the two.
☐ Chrome extension - AI assistance in any browser context. Crucial for support teams, researchers, and anyone working across web apps.
☐ API / SDK - Programmatic access for engineering teams to embed agents into internal tools, products, or workflows.
AI workspace pricing is one of the most confusing parts of any evaluation. Most platforms bundle model costs into the seat price, making it impossible to understand what you're actually paying per token. Others advertise BYOK but charge a surcharge on top.
☐ Transparent model pricing - Can you see exactly what you pay per model per token, or is it opaque bundled pricing?
☐ BYOK with zero markup - BYOK at zero surcharge — not "BYOK available at 10% markup."
☐ Free tier for pilots - A meaningful free tier (not a 7-day trial) allows proper evaluation before committing budget.
☐ No seat minimum for standard plans - Avoid platforms that require 100+ seat commitments before you can try a paid tier.
☐ Annual and monthly billing options - Annual for committed deployments. Monthly for pilots and smaller teams. Both should be available.
☐ VPC/single-tenant option - For companies that can't run on multi-tenant cloud. This should be an Enterprise option, not the only option.
☐ On-prem deployment option - Required for some regulated industries and government-adjacent organizations.
☐ Credits carry over on conversion - Any unused free-tier credits should apply toward a paid plan. No penalty for upgrading.
Add up your checked items. Here's how to interpret your results:
40–47 checked: The platform covers enterprise needs comprehensively. Focus your remaining evaluation on deployment speed, support quality, and integration depth for your specific stack.
30–39 checked: Solid in some areas, gaps in others. Map the unchecked items to your specific risk areas — if your CISO's requirements are unchecked, that's a hard blocker.
Below 30 checked: This platform likely covers one or two use cases well but isn't positioned as true enterprise AI workspace infrastructure. You may end up needing multiple tools where one governed platform should suffice.
An AI workspace isn't just a chat tool with extra features. The platforms that drive real enterprise value are the ones that treat governance as a foundation — not a feature tier — and extend beyond chat into agents that take action in the systems where work happens.
The checklist above represents 47 things that separate a mature enterprise AI workspace from a well-marketed chatbot. The right platform should clear most of them.
OrgLogic was built against exactly these requirements: multi-model chat at $8/seat, named AI agents with Skills and Connectors, and full IT governance on every plan — including Free. 600+ enterprise deployments across companies like Snowflake, Spotify, Snap, and Rakuten.
Single-model AI tools lock you into one provider at $25-60/seat. OrgLogic is a multi-model AI workspace with named Agents that act in your systems (Salesforce, Jira, Confluence, ServiceNow), packaged Skills for domain expertise, and full governance at $8/seat. You get every model, not just one.
Bring Your Own Key means you connect your own API keys from OpenAI, Anthropic, Google, or any provider. Your data flows directly to the model provider. OrgLogic never sees, stores, or processes your prompts or responses. Zero surcharge on your own keys. This is the #1 requirement for security teams evaluating enterprise AI platforms.
An Agent is a named AI worker with a defined job, connected to your systems via Connectors. A Skill is packaged expertise that teaches an Agent how to do specific work consistently. Unlike a generic chatbot, a Deal Prep Agent with a Salesforce Connector pulls real CRM data and produces structured call briefs. Skills are reusable across Agents, versioned, and authored in plain language.
Every Workspace includes per-Agent Connector permissions (each Agent gets scoped access, not blanket access), Agent-level audit trails, automatic PII redaction, per-team budget controls, model-level access controls, and configurable guardrails. Governance is the default environment on every plan, including Free. SOC 2 Type II, ISO 27001, HIPAA, and GDPR compliant.
The Free plan covers 25 users with $500 in credits ($20 per active user, pooled). The Business plan is $8/seat/month (annual) or $10 monthly. The seat fee covers the full platform: Agents, Skills, Connectors, governance dashboard, 5 surfaces, and all features. Model usage is separate: BYOK at zero surcharge, or OrgLogic-managed models at cost + 6%.
80% of employees already use AI tools without IT approval. OrgLogic replaces fragmented, ungoverned tools with one AI workspace employees actually want to use, available on web, Slack, Teams, Chrome, and API. One customer, a regulated tech company with 1,500 employees, reduced shadow AI by 91% within 6 weeks while cutting AI spend by 70%.
OrgLogic Connectors integrate with Salesforce, Jira, Confluence, ServiceNow, SharePoint, Google Workspace, Slack, SAP, and more via custom APIs. Each Connector has per-Agent permission scopes controlled by IT, so your Deal Prep Agent only accesses the Salesforce objects you approve. The Connector library is growing and new integrations ship regularly.
Self-serve signup takes 30 seconds. Connect your API keys in 2 minutes. Deploy pre-built Agents for sales, support, engineering, HR, and legal on day one. The Free plan (25 users, full governance) lets you pilot without procurement. One customer had engineers adopting within 2 weeks across Slack and Chrome. Enterprise plans add SSO/SCIM, VPC, and on-prem deployment.
