Enterprise AI agents: frequently asked questions

Not necessarily. Your systems stay where they are, and there are two types of connector. Ingestion connectors copy data into your Enterprise Data Model, where it stays isolated within your controls, with residency and audit. Federated (MCP) connectors don't ingest anything: they query the source system in real time, on demand. Both types have their place, and many deployments use a mix.

Incremental sync keeps the Enterprise Data Model up to date as your systems change, and federated connectors query sources live, so agents work from current knowledge instead of a stale snapshot.

Custom connectors are available and typically take about two weeks to build. If the gap is a document type rather than a system, you can configure additional document types yourself, or our implementation team can do it for you.

No. Model choice is a core principle: you match each use case to the best-fit model and can adopt new models as they emerge without re-architecting.

You route routine tasks to efficient models and reserve premium models for high-value work, which keeps inference spend aligned to the value each task delivers.

Outputs are grounded in your data and ontology and evaluated against your own success metrics, so you can tune and choose models based on measured results.

Yes, through governed plug-ins scoped by least-privilege access, with every action audited, so agents act safely and within policy.

Not every time. Plug-ins extend the platform without rebuilding it, and tested plug-ins are reusable across teams, so each new capability doesn't start from scratch.

Yes. Plug-ins are reusable, so a capability built for one use case can be shared across the organization.

Revenue Intelligence works from your CRM, contracts, product and usage data, and shared drives, brought together in the Enterprise Data Model. Customer Relationship Intelligence and the Customer 360 Dashboard give every rep one view of each account, with the reasons behind every signal.

It matches each RFP or DDQ question to your approved answer library, drafts every response with a citation, and flags the requirements you can't yet meet, so you can decide whether to bid. Proposal Generator works the same way for proposals, from your templates, pricing and product content, ready for your review.

The Upsell/Cross-sell Maximizer compares what each account owns with similar customers and what it has asked for, then ranks the best expansion opportunities with the evidence for each. Win/Loss Analyzer shows the patterns behind won and lost deals. A custom agent can compare contracted products and licenses with actual usage to find revenue leakage.

They work from your brand guidelines, positioning, approved language and product knowledge. Campaign Content drafts emails, social posts and landing-page copy in your brand voice, and Consistent Messaging checks new content against your positioning and suggests edits wherever it drifts.

Claims Check compares product and pricing claims with your approved product information before content goes out, and flags each mismatch with the source you need to fix it. Every output is logged for review.

Content Repurposing turns a white paper or webinar into blog posts, social snippets and email copy, keeping your approved wording intact. SEO Briefs builds each brief from the questions buyers ask and the content you already have, and Market Insights turns analyst reports, competitor launches and market news into a short brief.

Policy Q&A answers questions about leave, benefits or expenses in plain language, with a citation to the exact page of the policy. Onboarding Guide does the same for new hires' questions about tools, people and processes, and Employee Requests drafts policy-aligned replies to common requests for HR to check and send.

No. Application Summaries summarizes each application against the criteria you set and cites the evidence for every criterion. It doesn't rank or reject anyone: a recruiter reviews every application and makes every hiring decision.

Role-based access limits what each agent and user can reach, and every action is logged for audit. Role-based Learning and Engagement Themes work from your HR system within those same permissions, suggesting learning matched to each role and grouping survey comments into themes.

Yes. Cogito AI connects to the systems your teams already use, and its agents can run alongside other AI tools. How they fit together depends on your systems and governance, so talk to us about your setup.

No. Each solution comes with ready-to-deploy agents, which you tailor to your workflows. You can also import agents you've already built, or create new ones with the Agent Builder.

You set which data, models and users each agent can reach, guardrails screen every prompt and response with trip levels you choose, and every agent action is recorded in a searchable audit trail.

You choose which models are available to your users and agents, set a default for each agent and switch whenever a better fit launches, with no lock-in. For the highest levels of security, open-weight models can run in a completely ring-fenced manner. None of your data is sent to consumer AI services or used to train public models.

In the region you choose. Cogito AI is SOC 2 attested, with 100+ controls continuously monitored, data encrypted at rest and in transit, and a full audit trail on every agent action.