Phoenix AI Core sits on top of SAP, ServiceNow, Salesforce, and Oracle — not in place of them. Four pillars, one control plane: model serving, cross-system automation, unified retrieval, and policy enforcement on every AI action. Below is how each works and the value it returns.
Applications, agents, and copilots sit on top. The Phoenix AI Core sits in the middle as one control plane. SAP, ServiceNow, Salesforce, and Oracle stay exactly where they are — reached through governed connectors, never migrated. Phoenix is not a new system of record and does not replace any of them.
Almost no enterprise runs SAP, ServiceNow, or Salesforce in isolation. The processes that cost money to run badly — order-to-cash, case-to-resolution, procure-to-pay — span all of them. Every vendor's own AI stack is strong inside its walls and blind outside them.
SAP Joule, ServiceNow AI Control Tower, and Salesforce Agentforce each govern only their own platform. Phoenix's only reason to exist is being the layer that spans all of them — a position single-vendor stacks can't take without abandoning their own platform's gravity.
Native connectors into SAP, ServiceNow, Salesforce, and Oracle. Each stays the system of record; Phoenix reads and acts through governed scopes. Value on day one, layered on systems that already work.
Every agent action — SAP, ServiceNow, or Salesforce — is architecturally impossible without clearing policy first. Enforcement at the point of execution, applied uniformly, not a dashboard of what already went wrong.
Workload- and connector-based pricing published up front — not a quote gated behind a multi-month enterprise sales cycle. Build a budget before the first meeting, not after.
See a real cross-system workflow run live in a short demo. Production in weeks, operated by your own platform team — not a permanent embedded engineering squad on-site to keep it running.
Full in-region and air-gapped deployment for markets where hyperscaler dependency or cross-border data flow is a legal blocker — the reality for the multinational SAP / Oracle base this is built for.
The serving layer that runs your models. It deploys, fine-tunes, and hosts large language models and classical ML behind a single API — so the same governed model access powers every downstream agent and copilot, regardless of which connected system triggered it.
A vLLM / TGI serving layer with batching, KV-cache reuse, and speculative decoding on GPU pools targets sub-100 ms first-token latency with predictable throughput under load.
A policy layer routes each request to the cost-optimal model that meets the quality bar — Claude API alongside open models — with automatic failover across providers and regions.
LoRA / QLoRA and full fine-tuning pipelines adapt open and commercial models to your domain language, tone, and tasks without training from scratch.
Run in Phoenix cloud, your VPC, or fully on-prem / air-gapped. The same API and tooling works everywhere, so data residency is a config choice, not a rebuild.
Traffic-aware scaling, per-team and per-connector token budgets, and hard spend limits keep inference cost bounded and attributable to the workload that spent it.
Every call is traced — latency, tokens, cost, and quality-eval metrics — through OpenTelemetry to your dashboards and alerting, tagged by connector.
The orchestration layer that turns a model into a worker. Agents plan and execute multi-step processes across connected systems through a governed tool catalog — an SAP RFC call, a ServiceNow table update, and a Salesforce API action are all just scoped, audited tools — with human approval gates for high-value actions.
A stateful planner breaks a goal into ordered steps, chooses a tool for each, and adapts as results come back — no hard-coded flowchart per process.
Every read and write is a discrete registered tool with a schema, scope, and rate limit — never open-ended API access. An agent can only do what a specific tool explicitly allows.
Connectors run under least-privilege credentials — never a standing admin account into SAP, ServiceNow, or Salesforce — with every call attributable to an agent and a user.
Configurable approval thresholds pause the agent for sign-off on high-value or low-confidence actions, with the full cross-system context handed to the reviewer.
Long-running workflows persist state, survive restarts, and can be paused, replayed, and audited step by step.
If a connector is unavailable, the workflow serves last-known-good synced data with a staleness indicator rather than blocking the whole process.
The memory layer. It ingests and links records from SAP, ServiceNow, Salesforce, Oracle, and document stores into one permission-aware graph — so a query resolves a customer's full context, CRM case, support ticket, and ERP invoice, in one place instead of three.
SAP (BTP, OData, RFC, IDoc), ServiceNow (REST / Table API, Integration Hub, MID Server for on-prem), Salesforce (REST & Bulk API 2.0, Platform Events), and Oracle (OIC) feed the graph on a configurable sync cadence.
A Salesforce Account, a ServiceNow Company record, and an SAP Business Partner are resolved to one customer entity — so agents and queries reason about the real-world thing, not three copies of it.
A graph store (Neo4j-class) plus a vector index (pgvector / OpenSearch) combine graph traversal, semantic similarity, and keyword search — the basis for accurate, grounded answers.
Source-system access rights travel with the data. A user or agent only ever retrieves what it is entitled to see in the system the record came from.
Incremental sync keeps the graph current; every fact carries its source system, timestamp, and confidence so answers cite back to the exact record.
Applications and agents ask questions through a single semantic API instead of integrating SAP, ServiceNow, and Salesforce separately for every use case.
The control layer that wraps everything else. Identity, guardrails, immutable audit logging, and policy-as-code are enforced on every AI interaction across every connected system — giving compliance one control plane instead of three.
SSO / SCIM integration (Okta, Entra ID) with OAuth2 + OIDC ties every request to a user or service identity, with role-scoped access to models, tools, and connectors.
Rules evaluate every action and resolve to block, require approval, or log — enforced at the point of execution, uniformly across SAP, ServiceNow, and Salesforce.
Input and output screening for PII, secrets, prompt injection, and off-policy topics — configurable per application and per connector.
Every prompt, retrieval, tool call, and response is written append-only — never updated or deleted — attributable to SAP, ServiceNow, and Salesforce individually and to the overall transaction.
Automated quality, bias, and drift evals run against golden datasets, with per-connector policy-decision tracking and alerts when a model regresses.
Field-level encryption, permission inheritance from source systems, and a SOC 2 Type II certification path built into the roadmap.
"Resolve this customer's billing dispute" — a Salesforce case, a ServiceNow ticket, and an SAP invoice — handled as one governed workflow.
The user's identity, role, and data-access rights are resolved across every connected system before anything runs. Guardrails and policy for this application are attached.
The Salesforce case, the ServiceNow support ticket, and the SAP invoice and payment history are retrieved through hybrid search — filtered to what this user may see, each citation linked back to its source system.
The agent checks the SAP invoice via the SAP connector, drafts a resolution, and validates it against refund policy — pausing for human approval if the amount exceeds a threshold.
Each planning, extraction, and drafting call is routed to the right model at the right cost, with latency guarantees and automatic failover.
The full trace — context used, systems touched, decisions made, approvals — is written to the immutable audit log, attributable to SAP, ServiceNow, and Salesforce individually as well as to the overall transaction.
Each works from a single Phoenix surface instead of jumping between vendor consoles.
Connects SAP, ServiceNow, and Salesforce through the admin console, scopes credentials per connector, sets model-routing cost caps, and monitors connector health from one dashboard instead of three.
Builds an agentic workflow that spans systems — check SAP inventory, update a Salesforce opportunity, open a ServiceNow task for manual review — from the tool catalog, without custom integration code.
Reviews policy violations, blocked actions, and pending approvals across every connected system in one place, and pulls the immutable audit log for any transaction under review.
Uses a Phoenix copilot embedded in the ServiceNow workspace or Salesforce Lightning console — it pulls context from all connected systems and takes governed actions without the employee knowing which backend it came from.
Bring a real process that spans SAP, ServiceNow, or Salesforce. In a short demo we'll show inference, agents, knowledge, and governance handling it live — no slides.