Dome Systems vs Prefactor (2026)

The Tool Gateway is how agents act on outside systems. Admins attach MCP servers, REST APIs and internal services with their upstream authentication, OAuth included, and tools appear in a catalog for each agent, filtered by policy. Each call goes out through Dome with the credential injected at egress, so the agent never holds it, and customers can add tools of their own.

SourceDome Systems, domesystems.ai llms.txt (platform/gateway) and docs.domesystems.ai llms.txt (connect/resources/tools)read 2026-09-25

Agents built on LangChain, CrewAI, Anthropic, OpenAI and other stacks are instrumented through Prefactor's SDKs, framework middleware and OpenTelemetry support, so their steps flow in as spans. These bring telemetry in. Prefactor names no connector that lets an agent take authenticated action in an outside system through it.

SourcePrefactor, docs.prefactor.ai llms-full.txt (SDK overview, instrumentation strategy) and prefactor.tech llms-full.txtread 2026-09-25

The agent's own code owns the loop of model and tool calls, its steps and any handoffs. Dome sits at the call boundary and governs those calls without running the work. The agent lifecycle, from provisioned and active to suspended and revoked, is a state kept in the registry, and Dome has no workflow model.

SourceDome Systems, domesystems.ai llms.txt and docs.domesystems.ai llms.txt (concepts/agents/agent-lifecycle)read 2026-09-25

Steps, sequencing and handoffs belong to the agent's own framework. Prefactor records and scores what agents do and does not run their work, and it never ends a run on its own schedule. Agent versions and deployments across environments track releases, and Prefactor has no workflow model of its own.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Instance, Deployments and Versions tabs)read 2026-09-25

The customer's own scheduler, queue or event bus supplies the work, and Dome does not start agents. In Dome's event driven deployment example, an EventBridge schedule fires a Lambda, and retries and concurrency belong to that trigger. Dome governs the tool call the handler then makes. Signed webhooks send Dome's own audit events outward and wake no agent.

SourceDome Systems, docs.domesystems.ai/tutorials/production/deploy-your-agent/event-driven and llms.txt (operate/webhooks)read 2026-09-25

Runs start in the customer's own code. The agent's integration registers each run when it starts, and the WebSocket stream sends updates about runs outward. Prefactor does not start agents, and it has no schedule, webhook or event of its own that wakes one.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Instance, Stream agent instance updates)read 2026-09-25

Tool and model calls are governed, but none of the customer's documents are indexed for an agent to ground its answers on. Guards inspect content as it passes through and do not retrieve anything from the customer's corpus.

SourceDome Systems, domesystems.ai llms.txtread 2026-09-25

Grounding sits outside the product. Prefactor records and scores agent runs, and it indexes none of the customer's documents for an agent to ground its answers on. There is no retrieval structure over the customer's corpus.

SourcePrefactor, docs.prefactor.ai llms-full.txtread 2026-09-25

The registry, rules, quotas and audit events are records about agents. The platform and people apply or read them, and the agent never reads them as context to decide. Model Broker pools can cache responses to save cost and latency. Dome names no memory layer.

SourceDome Systems, domesystems.ai llms.txt (platform/registry, platform/broker)read 2026-09-25

Run records, risk scores and quality results are kept about agents, and the agent never reads them as context to decide. Prefactor describes no memory layer.

SourcePrefactor, docs.prefactor.ai llms-full.txtread 2026-09-25

Every tool and model call is checked against Cedar rules at the call boundary before it executes, failing closed with forbid winning by default. Rules can be scoped from the organization and tenant down to a workspace or a single agent, and they ship as versioned code. Guards inspect, redact and constrain content on tool and model connections, and quotas cap spend, tokens or calls. These controls stop an action outright. Decisions are made by policy, and Dome names no step where a person approves an action.

SourceDome Systems, domesystems.ai llms.txt (platform/authorization) and docs.domesystems.ai llms.txt (govern/guards, reference/mcp/quotas)read 2026-09-25

The oversight control is manual. While a run is active, an operator can terminate it from the agent instance page with a stated reason, and the agent's integration winds the run down. Risk profiles classify each run from the capabilities its spans declare. Crossing a threshold does not automatically block or terminate a run, because the classification is a label for human review and enforcement remains with the customer's team. Prefactor's pricing advertises real time hold, approve or block, which its docs contradict. Prefactor describes no approval step or guardrail beside the stop control.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Agent instance page, Risk tab, Risk profile) and prefactor.tech/pricingread 2026-09-25

Platform RBAC has built in and custom roles across organization, tenant and workspace scopes, with scoped platform API keys, all kept separate from runtime agent authorization. Every agent authenticates with the credential issued at registration. The end user an agent acts for is verified per agent through OIDC or HMAC instead of being trusted, so both identities reach each Cedar authorization decision and the audit record. Tools and models are reachable only through Gateways an admin grants, with upstream credentials injected at egress, so tool access is held to what is needed.

Dome names no attestation. For security measures the DPA points to trust.domesystems.ai, a Vanta trust center.

SourceDome Systems, docs.domesystems.ai llms.txt (manage/access, reference/permissions, concepts/platform/permissions, connect/agents/delegated) and domesystems.ai llms.txt (platform/access, dpa), plus trust.domesystems.airead 2026-09-25

Accounts can sign in through single sign on with the customer's identity provider, which comes with the Enterprise plan. API tokens are created per account and revoked when their creator is removed. All members of an account share the same level of access, with no role based permission distinctions. Prefactor publishes no attestation of its own. Its records can serve as evidence in a customer's own SOC 2, ISO 27001 or EU AI Act review.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Team tab, API tokens tab) and prefactor.tech/pricing and llms-full.txtread 2026-09-25

Every governed action emits an immutable audit event recording the agent, the caller chain and the tool or model, along with arguments, policy version and outcome, in one vocabulary across tool and model calls. Events can be queried from the UI and CLI or through the API and MCP server, exported as OCSF, CEF or CSV, and streamed continuously to a SIEM or exported in scheduled batches.

SourceDome Systems, domesystems.ai llms.txt (platform/audit) and docs.domesystems.ai llms.txt (manage/export, reference/events/catalog)read 2026-09-25

Each agent run is recorded as an instance with its full span timeline of LLM calls, tool calls, message turns and custom business steps. The record ties the run to the agent version and activity schema version that produced it and, where a profile is assigned, to the run's risk classification. Prefactor calls this chain the audit trail. The Activity tab and a WebSocket stream show runs and updates live. Sensitive fields can be encoded before they leave the agent. Data retention runs from 7 days on the free plan to 12 months on the upper plans.

SourcePrefactor, docs.prefactor.ai llms-full.txt (The audit trail, Agent instance page, Activity tab, WebSocket API, Sensitive encoding) and prefactor.tech/pricingread 2026-09-25

Four hosted tiers are sold. No hosting region is published, and no tier runs Dome itself in a VPC, in the customer's own environment or self hosted. Tenants are isolated logical environments inside an organization. The governed agents can run on any cloud or runtime, but Dome itself runs as a hosted service.

SourceDome Systems, domesystems.ai/pricing and llms.txt, and docs.domesystems.ai llms.txtread 2026-09-25

The service runs as managed cloud, and the Enterprise plan includes self hosted deployment. Prefactor describes no install steps, region or customer environment option. Dev, staging and production environments are logical environments inside the service.

SourcePrefactor, prefactor.tech/pricing and llms-full.txt, and docs.prefactor.ai llms-full.txt (Environments tab)read 2026-09-25

No ready made agents, workflows or templates ship. Tutorials and field guides walk a customer through building and deploying its own agents. Rules, guards and gateways are objects the customer writes.

SourceDome Systems, domesystems.ai llms.txt and docs.domesystems.ai llms.txt (tutorials)read 2026-09-25

Risk profiles can start from a preset that fills in weights. Prefactor ships no ready made agents, workflows or templates for a customer to adopt.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Risk page)read 2026-09-25

The Model Broker puts model choice with the customer. Admins connect providers such as Anthropic, OpenAI and Bedrock, or self hosted models, with their own credentials behind an API compatible with OpenAI and Anthropic. They compose them into pools with routing strategies, failover and caching, and set model choice as routing policy for each call.

SourceDome Systems, domesystems.ai llms.txt (platform/broker, llm-router field guide) and docs.domesystems.ai llms.txt (reference/mcp/models and pools)read 2026-09-25

Model choice stays with the agent's own framework. Prefactor records the model calls an agent makes but does not choose or route models. Its pricing includes optional bring your own LLM evals, but evaluation happens outside Prefactor, and Prefactor names no provider selection or customer model choice inside the product.

SourcePrefactor, docs.prefactor.ai llms-full.txt and prefactor.tech/pricingread 2026-09-25

Go and Python SDKs, a CLI and a REST API with a published reference drive the platform, with rules simulation at POST /v1/rules/simulate among the endpoints. An MCP server exposes Dome itself, with tools that register agents and attach tools and models, write rules, guards and quotas, and query audit.

SourceDome Systems, docs.domesystems.ai llms.txt (reference/surfaces/api, sdk, mcp and the MCP server reference) and domesystems.ai llms.txt (platform/operator)read 2026-09-25

An HTTP API and a WebSocket API cover the platform (with rate limits, sensitive field encoding and live instance streaming), alongside a CLI for environments and agents, agent skills, and Python and TypeScript SDKs with configuration, schema, rate limit and termination handling.

SourcePrefactor, docs.prefactor.ai llms-full.txt (HTTP API, WebSocket API, Prefactor CLI, SDK overview, Python SDK)read 2026-09-25

Authorization rules can be simulated against real replayed traffic and synthetic scenarios before they reach production, through the UI, CLI and API, and rules ship versioned through CI/CD. Simulation gates rule changes in the release path and shows how a new rule would decide the agent's calls. Dome names nothing that scores or tests the agent's own output.

SourceDome Systems, docs.domesystems.ai llms.txt (govern/rules/simulate, cli/secure/rules, api simulate) and domesystems.ai llms.txtread 2026-09-25

An agent's activity schema declares named quality schemas, and runs are marked as live, eval or smoke test. The customer's evaluation process submits its result after a run. The result shows on the run's Quality tab, with an optional summary template, and is recorded as quality spans. Prefactor does not produce these evaluations. The eval suite, grading model or human review happens outside it. The agent's own Quality tab shows run health over the last day, with success rate, typical and worst duration, and failures.

SourcePrefactor, docs.prefactor.ai llms-full.txt (Agent instance Quality tab, Agent Quality tab, Instance, Quality and performance) and prefactor.tech/pricingread 2026-09-25

Dome governs agents' tool and model calls and does not operate a browser or a computer.

SourceDome Systems, domesystems.ai llms.txt and docs.domesystems.ai llms.txtread 2026-09-25

Prefactor records and scores agent runs and does not operate a browser or a computer.

SourcePrefactor, docs.prefactor.ai llms-full.txtread 2026-09-25