Managed agent platforms for enterprise sales and RevOps teams

Revenue AI your team can audit before it acts.

TensorRev designs, deploys, and manages governed AI agent systems for revenue teams. Every claim is sourced or labeled, risky actions route to humans, and every workflow leaves an audit trail.

Implementation partner + managed platform - not a self-serve AI SDR.

managed-agent-replay.trace
est. $0.0000
01 Ingest02 Enrich03 Gate04 Human05 Export

Replay a governed revenue-agent workflow. Watch sources, rejected claims, evals, human gates, and the final brief appear in the trace.

sanitized replay - no customer data
Sourced or labeled
No unsupported claim should reach a buyer as fact.
Human gates
Judgment calls route to operators instead of being guessed.
Eval before action
Weak outputs are challenged before reps use them.
Audit log
RevOps and Legal can inspect the path from data to recommendation.
The problem

Revenue teams are being asked to trust AI they cannot inspect.

The issue is not whether a model can write. It is whether the organization can explain where the output came from, what data it used, which tools it touched, and who approved the action.

Black box

Confident output, unclear path

Generic AI sales tools produce polished recommendations without enough evidence for RevOps, Legal, or the field to defend.

Enterprise reality

Governance is the buying committee

CROs want action. RevOps wants control. Legal and Security want proof. A real system has to satisfy all three.

Managed agent platform

The operating layer underneath auditable revenue AI.

TensorRev is built around a governed agent platform: specialist agents, approved knowledge, tool permissions, evals, human gates, and replayable traces.

01
Orchestration
Route work across task-specific agents and hand off when judgment is needed.
02
Knowledge
Ground outputs in approved ICP, messaging, customer, and compliance sources.
03
Tools
Connect CRM, enrichment, public records, search, and exports with explicit boundaries.
04
Governance
Apply fail-closed gates, permissions, and human approvals before action.
05
Observability
Log sources, costs, model calls, rejected claims, evals, and operator decisions.
Use cases

Dead-lead recovery is one workflow. The platform is broader.

The same Glass Box pattern applies wherever revenue teams need AI-assisted action that can be inspected before it reaches a customer or prospect.

Pipeline recovery

Reopen stale opportunities

Find which cold or dead leads are worth another look, why now, and what a rep can safely say.

Account research

Rank and brief target accounts

Turn account lists into sourced briefs, fit scores, trigger narratives, and rejected-with-reason rows.

Buying committee

Map people and messages

Identify likely stakeholders, persona-specific angles, and the evidence behind each route.

Outbound enablement

Give reps inspected briefs

Generate outreach-ready handoffs with provenance chips, weak-claim removals, and human review states.

Signal monitoring

Watch for real movement

Monitor accounts for leadership, hiring, funding, regulatory, construction, or market triggers.

Portfolio coverage

Run repeatable coverage plays

Apply the same governed workflow across portcos, segments, regions, or priority account universes.

Proof

A trace your buying committee can inspect.

The strongest proof is not another AI-written email. It is the record of how the system found evidence, rejected weak claims, survived adversarial review, and escalated ambiguity to a human.

Sanitized Glass Box case

A real-style enterprise workflow, redacted for public review: source-first buyer discovery, identity checks, rejected enrichment, eval failure, correction, and human verification.

01Trigger-first search produced a candidate with source-backed fit.
02A plausible profile was withheld because identity did not reconcile.
03Adversarial review failed the first run and forced corrections.
04The corrected case passed and logged the human judgment step.

Why enterprise teams care

Every visible artifact is designed to answer the questions that stall AI in real sales organizations.

sourcedWhere did this claim come from?
rejectedWhat did the system refuse to use?
inferenceWhat is reasoned but not proven?
humanWhere did an operator approve or correct it?
Governance

Built for the people who have to defend the output.

Auditable AI is not a slogan. It is a set of controls that make revenue action safer to use, easier to inspect, and easier to improve.

sourced

Safe claims

Reps see which facts are supported before they put them in front of a buyer.

fail closed

No quiet hallucinations

Unsupported personalization is removed or routed to review, not polished into prose.

human gate

Judgment stays visible

Ambiguous signals become explicit operator decisions with a record attached.

audit trail

RevOps can inspect

Sources, model calls, costs, gates, and exports are traceable after the workflow runs.

Implementation model

Built with you, operated with governance.

TensorRev is an implementation and operating partner. We bring the platform, patterns, and build team; your revenue workflow supplies the context and approved data.

01

Map the workflow

Define the revenue action, risk boundaries, success criteria, and escalation points.

02

Connect sources

Wire CRM, enrichment, public sources, and approved company knowledge.

03

Configure agents

Set roles, tool permissions, evals, provenance states, and human gates.

04

Pilot on real data

Run a defined account or lead universe and review what passed, failed, or escalated.

05

Operate and improve

Monitor outcomes, capture rejects, update canon, and export into existing workflows.

How to start

Start with a workflow worth auditing.

A working session identifies where governed agents can create revenue action without creating brand, legal, or RevOps risk.

pilot4 weeks

Coverage Pilot

Run the managed agent workflow on a defined account or lead universe and deliver sourced briefs, reject ledgers, and audit logs.

Fixed scope, real data, clear pass/fail criteria.
Scope a pilot
campaignfree

Lead-Graveyard Teardown

A focused campaign path for teams that want to inspect cold or dead pipeline recovery first.

Still useful, no longer the whole company story.
Run the teardown
Straight answers

The questions an enterprise buyer should ask.

Both by design. TensorRev brings a reusable managed-agent platform and implements it around your revenue workflow, data, policies, and review model.

AI SDRs usually optimize for autonomous sending and volume. TensorRev optimizes for governed revenue action: sourced claims, human gates, evals, and audit logs before anything reaches a buyer.

Approved ICP docs, messaging, customer patterns, compliance rules, and deal history become the canon the agents retrieve from and are checked against.

It fails closed. The system labels uncertainty, rejects unsupported claims, or routes the decision to a human instead of inventing a confident reason to act.

A defined workflow run on your data: scored accounts or leads, sourced briefs, outreach-ready handoffs, rejected-with-reason lists, and an audit trail your team can inspect.

See a revenue workflow your team can audit.

Bring one account motion, lead segment, or outbound workflow. We will map where governed agents can help, where humans need to stay in the loop, and what proof your buying committee will need.