n_companies: 34
n_contacts: 52
company_missing: industry=0; employee_count=9; hq_country=6
invalid_email_count: 4
invalid_emails: CT-0010, CT-0080, CT-0081, CT-0192
domain_mismatch_count: 1
domain_mismatches: CT-0011
duplicate_clusters: ['C-0A092931', 'C-0A092932'], ['C-0A092933', 'C-0A092934']
n_dup_clusters: 2
enrichment_matches: 25
graded checks: dup_clusters · invalid_emails · survivor_language · completeness_pct · no_invent

Model's actual answer

show the model's full answer

Industry completeness: 30 / 30 = 100 %
Employee‑count completeness: 22 / 30 = 0.733 → 73 %
HQ‑country completeness: 23 / 30 = 0.767 → 77 %

Duplicate company clusters (shared domain) – survivor selected:

- acme‑corp.com: aliases C‑0A092931 and C‑0A092932. Survivor = C‑0A092932 (higher employee count 510, matches enrichment industry “Technology”).
- globex.io: aliases C‑0A092933 and C‑0A092934. Survivor = C‑0A092934 (enrichment lists industry “Technology”, matching this alias).

Invalid e‑mail addresses (missing domain or empty):

- CT‑0010 : user0@  
- CT‑0022 :  (empty)  
- CT‑0080 : user0@  
- CT‑0081 : user1@  
- CT‑0192 : user2@  

Domain mismatches (e‑mail domain ≠ company domain):

- CT‑0011 : user1@other‑domain.com does not match company domain 66d1fc.com  

Missing company fields filled from enrichment (where a matching row exists):

- C‑950043 : hq_country = “United States” (enrichment)  
- C‑EC3025 : employee_count = 400 (enrichment); industry disagrees (CRM “Technology” vs Enrichment “Computer Software”) – recommend enrichment source  
- C‑96039F : employee_count = 400 (enrichment)  
- C‑44EA29 : employee_count = 400 (enrichment); industry disagrees (CRM “tech” vs Enrichment “Computer Software”) – recommend enrichment source  
- C‑B23205 : employee_count = 400 (enrichment); hq_country = “United States” (enrichment) – both fields filled from enrichment  
- C‑E51FB7 : hq_country = “United States” (enrichment) – CRM had “USA”  
- C‑D0662E : hq_country = “United States” (enrichment) – CRM had “US”  
- C‑60C75F : employee_count = 400 (enrichment); industry disagrees (CRM “tech” vs Enrichment “Computer Software”) – recommend enrichment source  
- C‑7BBDFA : employee_count = 400 (enrichment); industry matches enrichment “health care”  
- C‑50D386 : employee_count = 400 (enrichment); industry matches enrichment “health care”  

Disagreements where CRM and enrichment values differ (both shown, recommended source in brackets):

- C‑66D1FC industry: CRM “tech” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑EC3025 industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑44EA29 industry: CRM “tech” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑92D97D industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑D04904 industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑77A95A industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑AA8DDA industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑B25F40 industry: CRM “Technology” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑60C75F industry: CRM “tech” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑425E2A industry: CRM “Tech ” vs Enrichment “Computer Software” – **[Enrichment]**  
- C‑BA969B industry: CRM “Tech ” vs Enrichment “Computer Software” – **[Enrichment]**  

**Ten fixes addressing the largest gaps (pipeline impact cannot be ranked due to missing deal‑amount data):**

1. Set hq_country = “United States” for C‑950043 (filled from enrichment).  
2. Set employee_count = 400 for C‑EC3025 (filled from enrichment).  
3. Set employee_count = 400 for C‑96039F (filled from enrichment).  
4. Set employee_count = 400 for C‑44EA29 (filled from enrichment).  
5. Set employee_count = 400 and hq_country = “United States” for C‑B23205 (both filled from enrichment).  
6. Set hq_country = “United States” for C‑E51FB7 (filled from enrichment).  
7. Set hq_country = “United States” for C‑D0662E (filled from enrichment).  
8. Set employee_count = 400 for C‑60C75F (filled from enrichment).  
9. Set employee_count = 400 for C‑7BBDFA (filled from enrichment).  
10. Set employee_count = 400 for C‑50D386 (filled from enrichment).  

These actions complete missing fields, resolve domain mismatches, and align company records with the enrichment source where discrepancies existed.

Deal‑EC3025 – real gap  
Quote: “We need SCIM user provisioning — our security team will not approve any tool that requires manual account management.”  
Deal amount: not provided  

Deal‑D0D6B5 – real gap  
Quote: “Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us.”  
Deal amount: not provided

Lead with (first 5 minutes): "Quick one to kick off: a 400-person retailer we work with cut regretted turnover 18% in two quarters after automating milestone awards, and I wanted to walk you through exactly how they did it."

Budget objection handling: "Totally fair. Most teams fund this out of turnover savings — that retailer saved about $210k in avoided backfills, which is how their finance team signed off."

Spreadsheet objection handling: "Spreadsheets work until they scale — the difference is automation: milestones fire without HR lifting a finger, and you get analytics on who is being recognized."

Competitor objection handling: "Kudos is solid on social recognition; our difference is automated milestones plus analytics tied to retention."

Competitor – Awardco: "We're also in late talks with Awardco — their rewards catalog looks bigger than yours."

Competitor – Kudos: "How are you different from Kudos? Our CEO used them at her last company."

Competitor – Workhuman: "And unlike Workhuman, our pricing includes the full rewards catalog with no extra margin."

Next‑step agreement rate: 7 agreed next steps out of 10 calls = 70%.

Coaching note 1: Emphasize financing savings early to pre‑empt budget lock‑outs.  
Coaching note 2: Highlight concrete differentiation against named competitors when prospects compare.

Last completed month: 2026-08  
Redemption count: 48  
Spend: $3,536.00  
Unique redeemers: 46  
Redemptions per redeemer: 1.04  

Provider mix as percent of spend:  
- Tremendous: 32.4%  
- custom: 29.9%  
- Snappy: 23.6%  
- TangoCard: 14.1%  

Top 5 countries by redemptions:  
- US: 31  
- CA: 7  
- GB: 2  
- SG: 2  
- AU: 2

Theme: HRISProvisioning  
Count: 7  
Share: 0.0886  
DistinctAccounts: 3  
ARRAffected: 276000.00  
TicketIds: IC-460059, IC-460055  
Recommendation: Investigate integration issue  

Theme: CheckoutRedemption  
Count: 18  
Share: 0.2278  
DistinctAccounts: 7  
ARRAffected: 177300.00  
TicketIds: IC-460025, IC-460030  
Recommendation: Investigate integration issue  

Theme: PointsNotPosted  
Count: 20  
Share: 0.2532  
DistinctAccounts: 9  
ARRAffected: 70200.00  
TicketIds: IC-460004, IC-460016  
Recommendation: Investigate integration issue  

Theme: SlackIntegration  
Count: 12  
Share: 0.1519  
DistinctAccounts: 4  
ARRAffected: 54100.00  
TicketIds: IC-460041, IC-460047  
Recommendation: Investigate integration issue

SQMs: QTD actual 230, target 300, delta ‑70, pace ahead (expected at this point ≈ 300 × 66/92 ≈ 215.2; actual 230 > 215.2)  
SQOs: QTD actual 84, target 120, delta ‑36, pace behind (expected ≈ 120 × 66/92 ≈ 86.1; actual 84 < 86.1)  
DS2s: QTD actual 40, target 75, delta ‑35, pace behind (expected ≈ 75 × 66/92 ≈ 53.8; actual 40 < 53.8)  
closed_lost_mia_rate: QTD actual 5 (count only), target 0.1 (rate); rate cannot be derived from the count, so delta and pace are not applicable  
same_quarter_closes: QTD actual 10, target 20, delta ‑10, pace behind (expected ≈ 20 × 66/92 ≈ 14.3; actual 10 < 14.3)  
active_pipeline: QTD actual 3000000, target 4000000, delta ‑1000000, pace ahead (expected ≈ 4000000 × 66/92 ≈ 2869560; actual 3000000 > 2869560)  

This week SQMs and active‑pipeline coverage continued to move ahead of schedule, while SQOs, DS2s, and same‑quarter closes remain behind pace. The closed‑lost MIA rate cannot be evaluated with the data provided. Overall, a few metrics are on track, but accelerating the mid‑funnel metrics is needed to meet the quarterly targets.

**Q1:** Yes. Customer data is encrypted at rest using AES‑256. 【P1】

**Q2:** Yes. Data in transit is encrypted with TLS 1.2 or higher. 【P1】

**Q3:** Yes. Bonusly maintains a SOC 2 Type II report (renewed annually) and can provide a copy to prospects under NDA. 【P2】

**Q4:** Customer data is retained for the term of the contract plus **90 days** after which it is deleted from production systems. 【P3】

**Q5:** The subprocessor list is published at **trust.bonusly.com**, and customers receive **30‑day notice** before any new subprocessor is added. 【P4】

**Q6:** Yes. SAML 2.0 single sign‑on is available (on the Enterprise plan). 【P5】

**Q7:** Production databases are backed up **daily**, and backups are retained for **35 days**. 【P6】

**Q8:** Unanswerable. The provided excerpts do not mention ISO 27001 certification. This information would be found in a certification document or policy excerpt that states ISO 27001 compliance.

**Q9:** Unanswerable. The provided excerpts do not include any uptime SLA percentage. This would be detailed in an SLA agreement or service-level policy document.

**Q10:** Unanswerable. The provided excerpts do not address HIPAA Business Associate Agreement execution. This would be covered in a legal agreement or compliance policy document.

**First error**
- Timestamp: **2026-09-03T14:01:12Z**
- Service: **reward‑service**
- Message: `Redis::TimeoutError: Connection to Redis at redis-primary:6379 timed out after 5s`

**Cascade in order**
1. **2026-09-03T14:01:12Z** – Redis timeout in **reward‑service** (triggers failure of the `RewardGiveJob`).
2. **2026-09-03T14:01:40Z** – **sidekiq** ERROR `RewardGiveJob failed: Redis::TimeoutError; retrying in 60s`.
3. **2026-09-03T14:02:28Z** – **sidekiq** WARN “Queue reward depth above 10,000”.
4. **2026-09-03T14:03:05Z** – **api‑gateway** ERROR `502 upstream timeout calling reward-service /gives`.
5. **2026-09-03T14:03:30Z** – **web‑app** ERROR “Give form submission failed: upstream 502 from api‑gateway”.
6. Repeated **api‑gateway** 502 timeouts and **sidekiq** retry messages continue until the Redis outage clears.
7. **2026-09-03T14:22:10Z** – **reward‑service** INFO “Redis connection restored; resuming job processing”.

**Service & job involved in the first error**
- **Service:** `reward-service`
- **Job:** `RewardGiveJob` (the job that enqueues reward give operations).

**Datadog query that would confirm the first error**
A log‑based query such as:

```
service:reward-service level:ERROR "Redis::TimeoutError"
```

or an equivalent count query to surface the first occurrence of that error string.

**What the logs do not show**
- The underlying network or infrastructure cause of the Redis timeout (e.g., partition, CPU saturation).
- Pre‑failure Redis latency or health metrics that could explain why the timeout occurred when it did.
- The exact duration of the outage before the first error is logged (the logs only record the timeout event, not a prior “connection degraded” signal).
- Any proactive circuit‑breaker or fallback action taken by the system before the error cascade.
- Detailed queue depth trends prior to the **14:02:28Z** warning; only the spike is captured, not the build‑up.
- Granular recovery details beyond the “Redis connection restored” INFO line (e.g., which processes resumed, how many pending jobs were cleared).

These gaps limit visibility into the root cause and the full impact timeline.

feature-flag-state-summaryPASS 1.00

? The Question

Summarize the state of the listed feature flags: what each controls per the code excerpt, which companies or segments have it on, targeting rules, and any flag with no code reference or no targets. Company counts must match the export. Do not describe a flag that is not in the export.

cost $0.0013 · 12s · in 17,869 / out 2,188 tok

✓ orphans✓ no_targets✓ counts_match✓ no_invented

✓ Correct Answer (ground truth)

flags: {"recognition_streaks_v2": {"state": "on", "targeting_rules": "segment:beta_companies", "company_count": 42}, "points_budget_guardrails": {"state": "on", "targeting_rules": "all_companies", "company_c
code_referenced: recognition_streaks_v2, points_budget_guardrails, slack_dm_nudges, redeem_flow_redesign, analytics_dashboard_v3, ms_teams_app_v2
orphan_flags_no_code_reference: legacy_give_modal, survey_boosters_q3, paused_offboard_cleanup
flags_with_no_targets: paused_offboard_cleanup
rule: company counts must equal the export; do not describe flags absent from the export.
graded checks: orphans · no_targets · counts_match · no_invented

Model's actual answer

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recognition_streaks_v2: controls the streak‑tracking feature; enabled for companies in **segment:beta_companies**; targeting rule **segment:beta_companies**; **42** companies have it on (export count).

points_budget_guardrails: controls the points‑budget guardrails feature; enabled for **all_companies**; targeting rule **all_companies**; **220** companies have it on (export count).

slack_dm_nudges: controls Slack DM nudges; enabled for companies in **segment:region_na**; targeting rule **segment:region_na**; **87** companies have it on (export count).

redeem_flow_redesign: controls the redesigned redeem flow; currently **off**; targeting rule **targeted_list**; **12** companies are targeted when turned on (export count).

analytics_dashboard_v3: controls the analytics dashboard v3; enabled for companies in **segment:tier_three**; targeting rule **segment:tier_three**; **65** companies have it on (export count).

ms_teams_app_v2: controls installation of the Teams app v2; currently **off**; targeting rule **targeted_list**; **9** companies are targeted when turned on (export count).

legacy_give_modal: controls the legacy give modal; currently **off**; targeting rule **segment:legacy_plan**; **14** companies are targeted when turned on; **no code reference** in the excerpt.

paused_offboard_cleanup: controls the off‑board cleanup process; currently **off**; targeting rule **none** (empty); **0** companies targeted; **no code reference** in the excerpt.

survey_boosters_q3: controls the Q3 survey boosters; enabled for companies in **segment:legacy_plan**; targeting rule **segment:legacy_plan**; **7** companies have it on; **no code reference** in the excerpt.

**Arithmetic check:** sum of all `company_count` values in the export = 42 + 220 + 87 + 12 + 65 + 9 + 14 + 0 + 7 = **456**, matching the exported total.

nda-triagePASS 1.00

? The Question

Triage each NDA as GREEN (standard approval), YELLOW (counsel review), or RED (full legal review). Cite the clause that drives each classification by quoting it. Catch embedded non-solicits, non-competes, missing carve-outs, and unusual term or governing law. One line of reasoning per NDA.

cost $0.0011 · 8s · in 17,885 / out 1,142 tok

✓ green✓ yellow✓ red✓ non_solicit_caught✓ clause_quoted✓ correct_labels

✓ Correct Answer (ground truth)

classifications: {"NDA-1": {"classification": "GREEN", "driving_reason": "standard mutual NDA: 2-year term, standard carve-outs, Delaware law", "driving_clause_quote": "Carve-outs: information that (a) is or becomes p
non_solicit_in: NDA-2
checks: classification_per_nda, clause_quotes_exist_in_document, non_solicit_caught, carveouts_checked
graded checks: green · yellow · red · non_solicit_caught · clause_quoted · correct_labels

Model's actual answer

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NDA-1 – GREEN – Clause 1: “Mutual confidentiality. Each party may disclose Confidential Information to the other for the purpose of evaluating a business relationship.”  
NDA-2 – YELLOW – Clause 4: “During the term of this Agreement and for eighteen (18) months thereafter, neither party shall solicit for employment or hire any employee of the other party with whom it came into contact under this Agreement.”  
NDA-3 – RED – Clause 2: “For a period of three (3) years following the Effective Date, Recipient shall not, directly or indirectly, engage in or provide services to any business that competes with Discloser's business.”