Your business runs on more than data. Eisberg runs on all of it.
Every other platform serves one side of your company. The warehouse serves the data team. Catalog tools document the data team's stack. Consulting-built ontologies arrive after months of services. Your project tracker sees Engineering. Your CRM sees Sales. Your chat tool sees comms. Eisberg combines structured business data + structured software/dev data + tribal knowledge in comms and docs — under one governed substrate, with one agentic OS that acts across all three.
What’s achievable — measured against your real workload
Three domains
Business systems + software systems + comms — combined
Auto-stitched
Cross-domain entities discovered by the ontology auto-linker
One audit chain
Every agent action across all three domains in one signed trail
What ships, in detail.
Business systems — the operational substrate
CRMs (Salesforce / HubSpot / Dynamics). ERPs (SAP / Oracle / NetSuite / Sage / Acumatica). HRIS (Workday / BambooHR / ADP). Billing + payments (Stripe / Recurly / Zuora). E-commerce (Shopify / BigCommerce / WooCommerce). Vertical SaaS (Procore / Toast / Bullhorn / Veeva / Epic / Guidewire / Yardi / Argus / CoStar). Whatever your function actually runs on — connected through one governed connector lifecycle, extended via the connector SDK.
Software systems — what your tech orgs use
Source code (GitHub / GitLab / Bitbucket). Issue tracking (Jira / Linear / Asana / Shortcut). CI/CD (GitHub Actions / CircleCI / Buildkite). Observability (Datadog / Grafana / New Relic). Cloud accounts (AWS / Azure / GCP). Infrastructure-as-code repos. PagerDuty + Opsgenie. Cloudflare + Vercel. The software domain lands on the same governed substrate — GitHub-class sources connected today, the rest arriving through the connector SDK.
Communication systems — where decisions actually happen
Slack + Microsoft Teams (channels + threads, consent-gated). Email (Google Workspace + Office 365). Meetings (Zoom + Google Meet via Recall / Otter / Gong / Chorus / Read.ai transcripts). Documents (Confluence + Notion + Google Docs + SharePoint). Wikis + runbooks. The 80% of business decisions that never reach the warehouse — captured as governed facts.
Cross-domain stitching — the entities no single tool can see
The CustomerImpact entity joining Salesforce.Account ↔ Jira.Issue ↔ Slack.#customer-escalations ↔ Zendesk.Ticket — auto-stitched by the ontology auto-linker. The SprintToRevenue entity joining GitHub.PR ↔ Linear.Issue ↔ Salesforce.Opportunity. The IncidentToRetention entity joining PagerDuty ↔ Slack.#incident-room ↔ Salesforce.Account.churn-risk. Eisberg surfaces relationships a tool confined to one domain can't — because no single tool is in all three domains.
One agentic OS over everything
Same signed Birth Certificate. Same Job spine. Same seven-policy plane. Same audit chain. A customer-impact agent reading both Salesforce.Account churn signal AND the Slack thread that escalated it AND the Jira ticket the AE asked Engineering to fix — and auto-paging the AE + EM if the impact score crosses a threshold. One audit trail, one approval policy, one billing event.
Why the assembled stack can't do this
Doing this requires (a) ingesting all three domain types, (b) auto-discovering cross-domain entities, (c) governing the whole stack with one policy plane, (d) running agents on a substrate that understands all three. Warehouse + catalog + ticketing + comms is four tools, four contracts, four governance models, and four sets of audit logs. Eisberg is one.
Other capabilities that compound with this one.
Want to see it live?
A 30-minute demo against your real data. We'll show you this capability end-to-end and answer any architecture or security question your team has.