SIGNLD vs Agentforce: one CRM vs every system

Agentforce is built to take action inside Salesforce, using the CRM data and Data Cloud it already sits on top of. SIGNLD is a decision intelligence platform that reasons read-only across every connected system, whichever vendor it comes from. The comparison is agents that act in one platform against a graph that reasons across all of them.

TL;DR

Agentforce is Salesforce's agent platform, built to take autonomous action inside Salesforce records using Data Cloud as its grounding layer. It is strongest where the workflow it needs to touch, a case, an opportunity, a lead, already lives in Salesforce. SIGNLD is a decision intelligence platform from Inzata Analytics that connects read-only to 800 plus business systems, including but not limited to the CRM, and builds a private Knowledge Graph without a modelling phase. Choose Agentforce when the action needs to happen inside Salesforce. Choose SIGNLD when the question spans systems Salesforce does not own.

For the wider context, see our roundup of the best decision intelligence platforms in 2026.

What does Agentforce do well?

Agentforce is a serious piece of engineering aimed at a specific job: letting an autonomous agent take action inside Salesforce on behalf of a service, sales, or marketing team. Because it is built by the vendor that owns the CRM's data model, it has native access to case records, opportunity stages, and customer histories without needing a separate integration step. An Agentforce agent can resolve a support case, update a record, or route a lead, and do it inside the same permissions and audit trail Salesforce already enforces.

Data Cloud, Salesforce's underlying data layer, extends this reach into other Salesforce clouds and select external sources that have been harmonized into it, which gives Agentforce a wider base than the CRM object model alone. For a company that runs its sales and service motion primarily through Salesforce, this is a meaningful capability. The agent is grounded in the same records a rep already works from, and action taken by the agent shows up in the same system the team already lives in, which keeps adoption friction low.

What Agentforce is built around is the assumption that the relevant data has been brought into Salesforce or Data Cloud, and that the useful outcome is an action taken inside that platform. Data that lives in an ERP, a separate ticketing tool, or a finance system outside that harmonization layer is not something Agentforce reaches into on its own.

What is decision intelligence, and how is it different?

An agent platform answers "what action should be taken inside this system." A decision intelligence platform answers "what is happening across all of our systems, and what should we do about it," before any action is taken anywhere. The difference is scope, and it is architectural rather than a matter of polish.

SIGNLD connects read-only to the systems a company already runs, ERP, CRM, ticketing, billing, and the spreadsheets finance keeps on the side, regardless of vendor, and resolves the same customer, order, or vendor across all of them inside a private Knowledge Graph. There is no modelling project and no requirement that data first be harmonized into one vendor's data layer. A COO asks a plain-language question and gets back a Decision Brief: the finding, evidence with links to the source records, a confidence signal, and a recommended action. Inference runs on a single-tenant AWS Bedrock instance, a private LLM never trained on your data.

The practical distinction is what happens after the answer. Agentforce is built to close the loop by acting inside Salesforce. SIGNLD is built to reason across every connected system first, read-only, and hand a person the evidence to decide, rather than assuming the relevant systems all sit inside one platform.

The same question, asked in both tools

Take a question a COO actually asks: why is customer churn rising in one segment. The real cause could be a support pattern logged in a helpdesk tool, a billing dispute recorded in finance software, a shipment delay tracked in the ERP, or a pricing change reflected in the CRM. All four systems are plausible sources, and in most companies they are not all Salesforce.

In Agentforce, the agent reasons well over whatever is inside Salesforce and Data Cloud. If the churn signal, the support tickets, and the CRM opportunity history are all there, an agent can identify accounts at risk and even trigger a retention workflow inside Salesforce automatically. If the billing dispute lives in a separate finance system and the shipment delay lives in an ERP that was never harmonized into Data Cloud, those causes sit outside what the agent can see, unless that integration work has already been done.

In SIGNLD, the COO asks the question directly. The Knowledge Graph already links the CRM's account history, the helpdesk's ticket volume, the finance system's billing disputes, and the ERP's shipment records, because those systems were connected read-only in advance with entities resolved across them. The Decision Brief comes back naming the shipment delay as the leading driver in that segment, with links to the specific ERP records and the billing disputes tied to the same accounts, a confidence signal, and a recommended action for the account team to work from.

Neither tool is wrong here. Agentforce acts fast and natively inside the system it already owns. SIGNLD reaches further across systems first, then leaves the action to a person equipped with the full picture.

What you build vs what you ask

	Agentforce	SIGNLD
what it models	actions and workflows grounded in Salesforce records and Data Cloud	business entities, metrics, and relationships resolved automatically across every connected system, regardless of vendor
who builds it	an admin or developer who configures agent topics, actions, and Data Cloud harmonization	no one authors it, entity resolution runs as part of each read-only connection
time to first cross-system answer	fast within Salesforce and harmonized Data Cloud sources, slower or not possible for systems outside that layer	minutes after the relevant systems connect
source traceability	traceable to the Salesforce record or Data Cloud source the agent acted on	citations back to the source record in the originating system, with a confidence signal
where inference runs	Salesforce's Agentforce models grounded in Data Cloud	a single-tenant AWS Bedrock instance, private LLM powered by AWS Bedrock, never trained on your data
who it is for	Salesforce admins and teams whose workflow runs primarily inside the CRM	a CEO, CFO, or COO at a 10 to 500 employee company with no dedicated data team

Pricing and who ends up owning it

Salesforce prices Agentforce on a consumption basis tied to conversations or actions, layered on top of existing Salesforce and Data Cloud licensing. Packaging and unit pricing have changed as the product has matured, so check the current published figures on Salesforce's site before budgeting. Ownership typically sits with the Salesforce admin team, since configuring agent topics, actions, and the Data Cloud harmonization behind them is specialized work that usually needs a dedicated owner.

SIGNLD's plans are listed on /pricing, with a Free Forever tier and a Growth trial that needs no credit card. There is no harmonization layer to build first, since entity resolution happens as part of connecting each system read-only. Ownership sits with the person asking the question, because there is no agent configuration estate that requires a specialist to maintain on their behalf.

Where Agentforce is the better choice

Agentforce is the better choice when the goal is autonomous action inside Salesforce itself. A service team that wants cases resolved without a human touching each one, or a sales team that wants leads routed and qualified automatically inside the CRM, gets real value from an agent that is native to that platform and already trusted with its permissions model. If your company's workflow lives inside Salesforce and the outcome you need is an action taken there, Agentforce is built for exactly that job.

SIGNLD's /why-us page is straightforward about this: it is not an action platform and it is not trying to replace what Agentforce does inside Salesforce. The two solve different problems. One closes the loop inside one CRM. The other reasons across every system a company runs before anyone decides what to do. A COO trying to explain churn that touches billing, support, and shipping systems outside Salesforce needs the second, and that is the specific gap this comparison covers.

Related reading: What is a knowledge graph for business, How SIGNLD builds a knowledge graph, what traceable AI for business analytics means, Decision Brief in the concepts glossary, and the difference between a dashboard and a decision cover the surrounding concepts in more depth. See also /connectors and /concepts for how SIGNLD reaches systems outside any single vendor's platform.

Key takeaways

Agentforce is Salesforce's agent platform, built to take autonomous action inside Salesforce records using Data Cloud as its grounding layer.
Take a question a COO actually asks: why is customer churn rising in one segment.
Agentforce is the better choice when the goal is autonomous action inside Salesforce itself.
Connecting your first system in SIGNLD takes about 15 minutes, with a first answer in minutes after that.
If Agentforce can act fast inside Salesforce but the real cause of a problem sits in your ERP or billing system instead, that gap is not an automation problem, it is a reach problem.

FAQ

Is Agentforce a decision intelligence tool?

Not in the sense this article uses the term. Agentforce is an agent platform built to take action inside Salesforce, grounded in CRM records and Data Cloud. It does not connect read-only across arbitrary outside systems and rank competing causal explanations with evidence attached.

Can SIGNLD replace Agentforce?

No, and it does not try to. Agentforce's strength is native, permissioned action inside Salesforce, which SIGNLD does not attempt to duplicate. SIGNLD is built for the cross-system reasoning that happens before someone decides what action to take, especially when the relevant systems are not all Salesforce.

Does Data Cloud let Agentforce reach outside Salesforce already?

Data Cloud harmonizes select external sources into a layer Agentforce can act on, which does extend its reach beyond core CRM objects. How far that extends depends on which sources have been harmonized and how much integration work that required, and it is worth checking Salesforce's current published connector list.

How fast is the first cross-system answer in SIGNLD?

Connecting your first system in SIGNLD takes about 15 minutes, with a first answer in minutes after that. That answer draws on entity resolution across every connected system, not on prior harmonization work into one vendor's data layer.

Who should buy SIGNLD instead of relying on Agentforce alone?

A CEO, CFO, or COO at a 10 to 500 employee company whose operational truth is spread across systems beyond Salesforce, such as an ERP, a separate ticketing tool, or finance software, and who needs an evidenced cross-system answer before deciding on action.

Try SIGNLD free

If Agentforce can act fast inside Salesforce but the real cause of a problem sits in your ERP or billing system instead, that gap is not an automation problem, it is a reach problem. Try SIGNLD free and connect a system in minutes, or Browse all articles for more on how decision intelligence compares to agent platforms.

SIGNLD vs Agentforce: agents inside one CRM vs agents across every system

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