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    AI lead enrichment in Salesforce.

    Most inbound leads arrive with two fields filled in: a name and an email. Reps spend the first ten minutes filling in the gaps before they can decide whether to engage. Ortoo Orchestrator enriches every lead on intake, attaches firmographic and behavioural context to the record, and surfaces what matters before the rep ever opens it.

    TEAMS RUNNING ON ORTOO ORCHESTRATOR

    IG
    Jaguar Land Rover
    Komatsu
    OppFi
    Sage
    Splunk
    Verivox
    Volvo
    IG
    Jaguar Land Rover
    Komatsu
    OppFi
    Sage
    Splunk
    Verivox
    Volvo

    What it is

    AI lead enrichment, in plain terms.

    AI lead enrichment in Salesforce means appending the data points a rep would otherwise look up manually, on every inbound lead, the moment it lands. Firmographics, behavioural signals, and intent context all attach to the record automatically.

    Enrichment sits inside Ortoo Orchestrator. AI is applied selectively for the signals that need interpretation, deterministic logic handles structured lookups, and every enrichment step is logged on the lead.

    The problem

    AI lead enrichment removes the research tax reps pay on every inbound lead

    Salesforce has the records and the events; what most teams still lack is the orchestration that turns AI from a one-off tool into a system. AI lead enrichment fixes the gap most revenue ops accept by default. A lead arrives with thin data. A rep digs through LinkedIn, the company website, and CRM history before they can decide whether to engage. Multiply that across every lead and the cumulative cost is real time off the calling block.

    Worse, the lookups vary. One rep fills in industry; another adds employee count; a third notes recent funding. The same lead, depending on which rep picks it up, ends up with different data in Salesforce. Reporting suffers and so does forecasting.

    Reps should be calling leads, not researching them.

    Ortoo Orchestrator enriches every inbound lead on intake. Firmographic data, behavioural signals, and intent context attach to the record before the rep opens it, with the workflow controlling which sources are used and how conflicts are resolved.

    // HOW IT WORKS

    Triggered by case context. Not by who is watching the queue.

    1. 01

      // STEP 01

      Every lead is enriched the moment it lands.

      Inbound leads trigger the enrichment workflow on creation. Configured data sources are queried in sequence or in parallel, depending on the rules the team set up.

      1. Lead created

        Thin record

      2. Query sources

        Sequence or parallel

      3. Resolve conflicts

        Source priority

      Step 01 — Lookup
      01
    2. 02

      // STEP 02

      AI reads the signals that need interpretation.

      Free-text intent, unstructured engagement data, and behavioural patterns sit better with AI. The workflow applies AI selectively for those signals, with deterministic lookups handling the rest. This step is handled by the enrichment agent inside Ortoo Orchestrator.

      1. AI on free text

        Intent, behaviour

      2. Deterministic lookup

        Firmographics

      3. Map to fields

        Standard + custom

      Step 02 — Append
      02
    3. 03

      // STEP 03

      Enriched data attaches to the lead, ready to act on.

      Firmographic fields, behavioural scores, and any AI-derived flags land on the Salesforce record. Routing logic can then read those fields when deciding which rep to match.

      1. Write to lead

        Fields populated

      2. Hand off to routing

        Same workflow

      3. Log lineage

        Source per field

      Step 03 — Surface
      03

    What good enrichment needs

    Three things separate working enrichment from a noisy field dump.

    Adding data to a lead is easy. Adding the right data, in the right fields, on the right schedule is what makes enrichment useful. Three things keep the workflow trustworthy. The path is operationally realistic: start with one workflow at a time, expand step by step as the team is ready.

    Book a demo

    Source conflict resolution

    Multiple data sources disagree. Define which wins, and capture the source so audit is traceable.

    Mapped to the routing rules

    Enrichment that does not connect to routing is data without consequence.

    AI on the signals that need it

    Use AI for interpretation, structured lookups for everything else. Cost stays bounded.

    Before vs after

    What changes when enrichment runs as a workflow.

    The data sources do not change. What changes is whether the data actually gets onto the record.

    Before

    Before

    1. 01Manual lookup
    2. 02Inconsistent fields
    3. 03Enrichment post-call
    4. 04Rep-led research

    Reps spend the first ten minutes filling in the gaps before they can decide whether to engage.

    After

    With Ortoo Orchestrator

    1. 01Auto-enriched
    2. 02Mapped fields
    3. 03Enrichment on intake
    4. 04Workflow-led research

    Reps open a lead with the context already attached and start the conversation.

    Where it fits

    Works with the Salesforce tools you already use.

    AI lead enrichment with third-party data providers

    Data providersIntegrations

    External data services (Clearbit, ZoomInfo, Apollo, etc.) plug into the enrichment workflow as data sources. The workflow handles the API call, the field mapping, and the conflict resolution, with the team choosing which providers run on which leads.

    AI lead enrichment for regulated industries

    Financial servicesHealthcare

    In regulated sectors, the enrichment decision often depends on data fields that must be sourced from a specific provider for compliance reasons. The workflow runs those checks against the right source every time, captures the inputs, and produces an audit trail.

    Enrichment feeding the routing decision

    RoutingLead assignment

    Enrichment that does not feed routing creates richer records that still get routed by the wrong logic. Inside Ortoo Orchestrator, enrichment fields are available to the routing capability in the same workflow step, so the right rep gets the right lead based on freshly attached data.

    Built for revenue operations

    Enrichment ops can own, end to end.

    Reps engage with context they did not have to find.

    When the workflow handles research, reps spend their time on the conversation. Talk tracks land sharper because the context is already on the record, and discovery calls start further along. Enrichment runs as one step in the workflow from intake to assignment.

    Pipeline data becomes consistent across reps.

    Every lead is enriched the same way. Marketing, sales ops, and leadership read the same fields, with the same definitions, on every record. Reporting accuracy rises without ops having to chase data quality manually.

    Specialised agents do the work, not a single generalist AI.

    Each step is owned by a specialised agent with a defined role, including the Enrichment Agent relevant to this workflow. Agents pass context between steps, AI is applied only where interpretation adds value, and deterministic logic controls the rest.

    IndustryEmployee countRevenueTech stackIntentFundingGeographyEngagementLookalike score

    Signals the enrichment workflow attaches

    Components of AI lead enrichment

    Four elements every enrichment workflow needs to cover.

    Ortoo Orchestrator provides the engine. Data sources, field mappings, and conflict rules are configured by revenue operations.

    Query data providers in sequence or parallel, with conflict resolution rules.

    // RULE CONFIG

    Enterprise inbound, multi-source enrichment

    trigger
    Lead created
    providers
    ZoomInfo, Clearbit
    AI signals
    Intent, sentiment
    conflict rule
    ZoomInfo wins on firmographics
    field mapping
    Industry, size, revenue
    audit
    Source per field

    IF segment = Enterprise THEN query ZoomInfo + Clearbit; AI reads intent text; ZoomInfo wins on firmographics.

    Case studies

    Teams running enrichment as a workflow.

    Related use cases

    Adjacent revenue workflows in Ortoo Orchestrator.

    FAQ

    Common questions

    Which data providers can we use?+

    Any provider with an API. Common integrations include Clearbit, ZoomInfo, Apollo, and 6sense. The workflow handles the API call, field mapping, and conflict resolution declaratively.

    What happens when providers disagree?+

    The team configures the conflict resolution rule per field. The workflow records which source was used so the lineage is traceable from the Salesforce record.

    Can we use our own LLM provider for the AI parts?+

    Yes. Bring-your-own-LLM is supported, so teams running an OpenAI, Anthropic, or Google enterprise contract route AI calls through their own provider, with costs and audit trails on their own bill.

    How is enrichment cost controlled?+

    Calls to external data providers happen only on the leads the workflow flags as worth enriching, based on rules the team set. Cost per lead is predictable and visible in Salesforce reporting.

    Does this require Apex or a developer to set up?+

    No. Source definitions, field mappings, and conflict resolution rules are configured declaratively inside Salesforce setup. Operations teams adjust the workflow without engineering involvement.

    Does enrichment feed the routing decision?+

    Yes. Enrichment runs in the same workflow as routing, so the routing capability inside Ortoo Orchestrator can read the freshly attached fields when matching the lead to a rep.

    Is the enrichment audit trail reportable?+

    Yes. Every enrichment step is logged with the source, the field, and the timestamp. Standard Salesforce reporting surfaces it automatically.

    Stop researching, start engaging

    Map the enrichment workflow your team should be running.

    Book a 30-minute conversation. We will walk through your current research workflow and where automation removes the lag.

    Installs natively into Salesforce. Start with one workflow, expand to others as the team is ready. Pricing follows work completed, not token usage.