10 agents in production
Every record unified
CRM, support, calls, enrichment, and web signals normalized into a single Revenue Ontology.
150+ providers active
Data Waterfall configured for your segments. 95%+ email, 80%+ phone. 30-40% lower enrichment cost.
Ontology already learning
Signal classifications calibrated. Scoring tuned. Schema evolving from how your team actually works.
w1
WEEK 1
Discovery & configure
Map CRM schema. Connect integrations. Configure Ontology, signal taxonomy, pipeline stages. Set up Data Waterfall.
w2
WEEK 2
Build & validate
Build first 3-5 agent workflows. Run outputs in staging. Review with your teams. Tune from feedback.
w3
WEEK 3
Production
Agents go live. FDE team monitors quality and accuracy daily. Issues fixed same-day.
∞
ONGOING
Compound
Monthly reviews. New agents deployed. Scoring tunes from conversions. Ontology evolves from drift detection.
SOC 2 Type II
GDPR compliant
DPAs, right to deletion, data portability, lawful basis documentation.
Single-tenant
Isolated compute, storage, indexes, vector stores. No cross-tenant join paths.
Network isolation
AWS PrivateLink. Data-plane traffic never touches public internet.
Permission-aware
Agents inherit invoking user's permission scope.
Full versioning
Point-in-time queries, diff inspection, full rollback.
what’s not
Per-seat fees
Per-call metering
Overage charges
Separate bills for support or onboarding
A pricing page with three tiers
Re-pricing when needs change
WHAT's INCLUDED
Forward-deployed engineering team
Single-tenant infrastructure
All agent workflows in your SOW
Data Waterfall within your volume tier
All integrations
Ongoing optimization & monthly reviews
Every enterprise customer gets an FDE team. Not professional services with an end date. Not a CSM who checks in quarterly. Engineers who live in your stack and stay with your account.
They configure your Ontology, build agent workflows, handle complex integrations, and tune scoring models from outcome data. Accountable for your results — month 1, month 6, month 12.
The gap between "we bought the tool" and "the tool works for us" is where most enterprise software dies. FDEs close that gap. Permanently. Your deployment doesn't stall.
How do you ensure data accuracy across multiple enrichment sources?
What happens if an agent makes a mistake?
How customizable are the agents?
Do we need internal engineering resources to use Lantern?
How does Lantern handle data privacy and compliance across regions?
Can Lantern scale with our growth?
What makes Lantern different from traditional RevOps tools?
