SalesManaged AI Agents

Sales AI Agents,
Monitored for Accuracy

Nestack Agent Care helps sales teams monitor, evaluate, and optimize AI agents used for lead qualification, outreach, quoting, and CRM updates — before small AI errors become inaccurate or off-policy commitments.

43failure modes
19SEV-1 failure modes
760+baseline eval cases
24/7Agent Monitoring

Scope

Sales AI agents we build & manage

Thirteen archetypes — from prospecting to speed-to-lead, deal-desk approvals and forecasting.

Lead generation3

  • Outbound prospecting & SDR
  • Inbound speed-to-lead
  • Lead-enrichment & routing

Closing deals5

  • Proposal & RFP-response
  • Quote/CPQ
  • Meeting-prep & follow-up
  • Deal-desk & approval
  • Contract-redlining

Pipeline & performance5

  • Pipeline-hygiene
  • Forecasting & revenue-signal
  • Conversation-coaching
  • Renewal & upsell
  • CRM data-entry

Observability

What we make observable

Every sales agent session is traced across ten layers — what we capture and the evidence we keep.

  1. Evidence we keep
    Goalconstraintsapproval requirement
  2. Evidence we keep
    Sourceversiontimestamprelevancecitation
  3. Evidence we keep
    Planned sequenceactual sequenceworkflow status
  4. Evidence we keep
    Task statusresultretryfailure reason
  5. Evidence we keep
    Tool nameversioninputoutputpermissionresult
  6. Evidence we keep
    Model/versioninput/outputtoken usagelatencycost
  7. Evidence we keep
    Evaluation typemetricthresholdresult
  8. Evidence we keep
    Guardrail targettriggeractionenforcement result
  9. Evidence we keep
    Reviewerdecisioncorrectionreason
  10. Evidence we keep
    Outcome statusbusiness resultlinked trace

Catalog

Failure modes

Filter failure modes by where they occur in the agent lifecycle—from goals and retrieval to tools, evaluations, guardrails and outcomes.

Nothing on this page matches that. Try a layer (tool, retrieval, guardrail), a code, or a severity.

0 documented↑↓ move · ↵ open · ⌘↵ filter matrix
43 documented · select a cell to filter
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SAL-01False or overstated product claims in proposals and outreachSEV-1
SAL-02Unauthorized discounts, terms or SLAs offeredSEV-1
SAL-03Cross-prospect data leakage — one account’s pricing/strategy to anotherSEV-1
SAL-04Pipeline-report hallucination — invented stages, values, close datesSEV-2
SAL-05Quote errors — pricing tiers, bundling, currencySEV-2
SAL-06Outreach-compliance violations — consent, opt-outs, calling hoursSEV-2
SAL-07Injection via prospect replies and uploaded RFP documentsSEV-1
SAL-08CRM corruption — notes on wrong opportunities, stages advanced without evidenceSEV-2
SAL-09Competitor disparagement — unverifiable knocks in outreach and battlecardsSEV-2
SAL-10Redline overreach — non-standard terms accepted beyond the playbookSEV-1
SAL-11Prospect misidentification — competitors, journalists or customers approached coldSEV-3
SAL-12Territory and routing violations — accounts double-touched across repsSEV-3
SAL-13Follow-up hallucination — invented commitments and next steps in recap emailsSEV-2
SAL-14Undisclosed-AI / bot-disclosure failure — agent passes as humanSEV-1
SAL-15Binding contract formation by an autonomous agentSEV-1
SAL-16Fabricated testimonials, reviews & customer logosSEV-1
SAL-17AI note-taker recording without consent & confidential over-captureSEV-1
SAL-18Algorithmic pricing collusion via pooled competitor dataSEV-1
SAL-19Unlawful data sourcing for prospecting — scraping & lawful basisSEV-1
SAL-20Automated lead-scoring bias — algorithmic redliningSEV-1
SAL-21AI-washing & AI-inflated pipeline in reported metricsSEV-2
SAL-22Third-party sales-AI integration breach — OAuth supply chainSEV-1
SAL-23Excessive agency via over-scoped CRM credentialsSEV-1
SAL-24Knowledge-base & battlecard poisoning (RAG)SEV-1
SAL-25Persistent memory & session-context contaminationSEV-1
SAL-26Insecure output handling — exfil links, XSS, phishing luresSEV-2
SAL-27Deepfake impersonation & agent-assisted BEC 2.0SEV-1
SAL-28MCP / plugin tool-poisoning supply chainSEV-1
SAL-29Shadow-AI sales tools on unmanaged accountsSEV-2
SAL-30KPI gaming — junk-meeting quota hacking (goal misgeneralization)SEV-2
SAL-31Sycophancy toward prospects — agreeing to false premisesSEV-2
SAL-32Strategic deception under quota pressureSEV-1
SAL-33Cascading multi-agent orchestration failure (SDR → CRM → quoting)SEV-2
SAL-34Human-in-the-loop rubber-stamping & approval fatigueSEV-2
SAL-35Silent model drift / regression after provider updateSEV-2
SAL-36Accountability & audit-trail gap — "who promised that?"SEV-2
SAL-37Self-disparagement — agent trashes its own company on the recordSEV-2
SAL-38Offensive or wrong hallucinated personalizationSEV-2
SAL-39Revenue cannibalization — outreach to existing customers & open oppsSEV-2
SAL-40Email deliverability collapse & domain-reputation burnSEV-2
SAL-41Stale-catalog actions — discontinued / EOL SKUs quotedSEV-2
SAL-42Meeting-scheduler timezone & double-booking failuresSEV-3
SAL-43Runaway agent loops — duplicate sends & cost blowoutSEV-2

Guardrails

Critical guardrails for Sales agents

Ten controls that hold regardless of prompt, plan or pressure. Open one to see what it protects, what trips it, what the agent is forced to do, who may release it, and what is written to the record.

GR-01No discount or terms beyond delegated authorityOverride defined
  1. Target

    Quote generation, proposal terms, SLA commitments and discount fields in CPQ and CRM

  2. Trigger

    Draft quote or reply exceeding the rep’s delegation-of-authority matrix for discount, term or SLA

  3. Action — enforced

    Platform holds the quote unsent and strips the offending term; agent may request approval or offer in-matrix alternatives.

  4. Human override

    Sales VP via deal-desk approval recorded against the opportunity id

Logged evidenceopportunity id · requested vs authorized discount · matrix version · approver identity · UTC timestamp

GR-02No cross-prospect retrieval of pricing or strategyNo override
  1. Target

    CRM records, quotes, battlecards and negotiation notes partitioned per account and opportunity

  2. Trigger

    Retrieval or generation referencing one account’s pricing, terms or strategy inside another account’s session

  3. Action — enforced

    Platform blocks the fetch and scrubs session memory of foreign-account content; agent may use only current-account records.

  4. Human override

    None — cannot be overridden in session

Logged evidencesession id · blocked record ids · account partition labels · memory-scrub hash · block timestamp

GR-03No instruction embedded in prospect replies ever executedNo override
  1. Target

    Inbound prospect emails, uploaded RFP documents, calendar invites and attachments the agent parses

  2. Trigger

    Imperative or tool-directing text detected inside any prospect-supplied message, document or attachment

  3. Action — enforced

    Platform neutralizes the content to quoted data and refuses execution; agent may summarize it and continue the deal.

  4. Human override

    None — cannot be overridden in session

Logged evidencemessage id · detected instruction span · sender domain · sanitized copy hash · detection timestamp

GR-04No binding contract formation by the agentOverride defined
  1. Target

    Order forms, e-signature workflows, acceptance language in emails and chat across all deals

  2. Trigger

    Draft output constituting acceptance, signature or agreement to terms on the company’s behalf

  3. Action — enforced

    Platform blocks the send and watermarks drafts non-binding; agent may prepare the contract for a human signatory.

  4. Human override

    Commercial director via the e-signature platform’s recorded signing ceremony

Logged evidencedraft hash · blocked clause list · opportunity id · signatory of record · block timestamp

GR-05No unsubstantiated capability claims in proposalsOverride defined
  1. Target

    Proposals, outreach copy, battlecards and demo scripts making product capability or customer-proof claims

  2. Trigger

    Claim, testimonial or logo lacking a match in the approved substantiation library

  3. Action — enforced

    Platform blocks the send and flags each unsupported claim; agent may substitute approved claims or request substantiation.

  4. Human override

    Product marketing lead via substantiation-library entry citing verifiable evidence

Logged evidencedocument id · flagged claim list · substantiation record ids · reviewer identity · review timestamp

GR-06No outreach to opted-out or non-consented contactsOverride defined
  1. Target

    Email sequences, dialers and SMS campaigns governed by CAN-SPAM, TCPA and Spam Act rules

  2. Trigger

    Send or dial targeting a suppressed contact, missing lawful basis, or outside permitted hours

  3. Action — enforced

    Platform blocks the send and quarantines the sequence step; agent may target only consented contacts within permitted hours.

  4. Human override

    Marketing-compliance officer via suppression-list correction with documented consent proof

Logged evidencecontact id · suppression-list version · consent record · attempted channel and time · block timestamp

GR-07No agent passing as human with prospectsOverride defined
  1. Target

    Chat, email, voice and SMS conversations where the counterparty could assume a human rep

  2. Trigger

    Conversation start, or direct question about identity, without an AI disclosure on record

  3. Action — enforced

    Platform injects the AI disclosure and blocks denial of bot status; agent may continue once disclosure is delivered.

  4. Human override

    Legal counsel via approved disclosure-script change logged in the policy register

Logged evidenceconversation id · disclosure text version · delivery timestamp · channel · counterparty query span

GR-08No call recording without all-party consentOverride defined
  1. Target

    AI note-takers and call-recording bots joining discovery calls, demos and negotiations

  2. Trigger

    Recording or transcription starting before every participant’s consent is captured for that jurisdiction

  3. Action — enforced

    Platform blocks capture and discards buffered audio; agent may restart recording only after every participant consents.

  4. Human override

    Sales-operations manager via jurisdiction-consent checklist completed before the call

Logged evidencemeeting id · participant consent states · jurisdiction rule applied · audio-discard hash · stop timestamp

GR-09No pricing set from pooled competitor dataOverride defined
  1. Target

    Pricing recommendations, discount guidance and win-loss models fed by external market data

  2. Trigger

    Recommendation input containing non-public competitor pricing or shared-vendor pooled market feeds

  3. Action — enforced

    Platform blocks the recommendation and purges the tainted feed; agent may price from public lists and internal costs.

  4. Human override

    General counsel via antitrust review clearing the data source in writing

Logged evidencefeed source id · data provenance record · blocked recommendation hash · counsel review id · purge timestamp

GR-10No approval accepted on voice likeness aloneOverride defined
  1. Target

    Deal approvals, payment-detail changes and executive requests arriving by voice, video or chat

  2. Trigger

    High-value instruction authenticated only by claimed identity, voice or video resemblance

  3. Action — enforced

    Platform holds the action pending out-of-band verification on a directory-listed channel; agent may prepare but not execute.

  4. Human override

    Finance controller via callback verification to the directory number of record

Logged evidencerequest id · claimed identity · verification channel and outcome · hold duration · release timestamp

Oversight

Human review — triggers, decisions and evidence

When a defined risk trigger fires, the affected action is routed to a named reviewer. Every decision is recorded with its correction, escalation and final outcome for full traceability.

  • ConfidenceLow-confidence pipeline read
  • Financial impactDiscount beyond playbook
  • Identity / change riskProspect identity check
  • Irreversible actionQuote or redline release
  • Policy riskOutreach-consent conflict
  • Safety controlGuardrail override
  • Quality failureFailed critical evaluation
Humanreviewnamed reviewer
  • Revieweridentity + role
  • Decisionapprove / reject / amend
  • Correctionwhat changed
  • Escalationwho, why and severity
  • Final outcomereleased / blocked / returned for rework

7 triggers · any one halts the agent

1 record · 5 fields, every time

Compliance

Regulatory mapping

  • 01 Goal
  • 02 Retrieval
  • 03 Workflow
  • 06 LLM
  • 07 Evaluation
  • 08 Guardrail
  • 10 Outcome

Claim law

product capability claims in proposals bind the company.

FTC / ACCC

Lifecycle layer:02 Retrieval · 06 LLM · 07 Evaluation

  • SAL-01

Evaluations

Baseline evaluation suite — in detail

Baseline evaluations are completed during onboarding and repeated based on the selected plan. Agents that fail critical checks remain restricted until they pass re-testing.

Detailed case sets
36
Failure modes covered
43
Retired & rotated / quarter
10%
Audit-ready scorecard
Monthly

Output evaluation2 suites · 140 cases

100 casesQuote accuracycatches SAL-05
40 casesTargeting-hygiene setcatches SAL-11

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  1. Department lead review

    For applicable high-risk agents, the client’s designated department leader reviews the evaluation criteria and pass thresholds before baseline approval.

  2. Test-case rotation

    Evaluation cases are refreshed regularly to reduce memorisation and maintain reliable performance measurement.

  3. Scorecard integration

    Scorecards track results against the approved baseline and flag material declines for review and escalation.

  4. Department-specific extensions

    Where included in scope, evaluations may be expanded using approved workflows, tools, templates, policies, and incident history.

Monitoring

Change-aware monitoring

When agent performance changes, Nestack correlates the shift with changes to the agent, prompt, model, tools, knowledge base, guardrails and evaluation suite.

Version changes by layer
01AgentAgent changed in week 4Agent changed in week 11
02PromptPrompt changed in week 6
03ModelModel changed in week 8Model changed in week 10
04ToolTool changed in week 3
05Knowledge-baseKnowledge-base changed in week 7
06GuardrailGuardrail changed in week 5Guardrail changed in week 12
07Eval-suiteEval-suite changed in week 10
Claim-accuracy rate92–100%
  • Week 1 · 98.5%
  • Week 2 · 98.4%
  • Week 3 · 98.6%
  • Week 4 · 98.5%
  • Week 5 · 98.7%
  • Week 6 · 98.5%
  • Week 7 · 98.6%
  • Week 8 · 94.2%
  • Week 9 · 94.0%
  • Week 10 · 98.5%
  • Week 11 · 98.6%
  • Week 12 · 98.7%

Week readouthover or select

Week 8of 12

  • 03Modelopus 4.6 · 0612

94.2%Claim-accuracy rate

  • 7 layers stamped on every run · 12-week window
  • Catches SAL-35 · silent model drift after a provider update

Something missing?

Don’t see your agent’s issue here?

Every AI environment is different. Share what you’re seeing, and we’ll review the behaviour, assess the risk and recommend the evaluations or controls that may help.

Report an agent issue

Tell us what you’re seeing

The more specific, the faster we can reproduce it. Playbook: Sales

We reply within one business day.

See pricing

No commitment. Even if you never become a client, we’ll tell you what we think is happening.

Process

Universal incident runbook

Severity is assigned based on business impact, customer harm, data exposure, operational disruption and overall scope.

  • SEV-1 Critical
  • SEV-2 Major
  • SEV-3 Moderate
  • SEV-4 Minor
STEP 01

Automated monitoring or human review identifies unusual behaviour. Alerts are recorded and routed according to severity.

Cost control

Keep sales AI agent costs under control

Token spend is monitored, optimised and reported as part of Agent Care — and savings never come at the expense of quality, because every change is verified against your evaluation baseline.

We review token spend by agent, workflow, model, and session so you can understand where AI costs are coming from.

Running sales AI agents in production?

Get a free assessment of one agent. We’ll review its behaviour, run a baseline evaluation and highlight potential risks and performance gaps.

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