PositivityTech® AI Risk Algorithms |
Tal Solutions LLC · Intelligence & Research
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 8 captures on record
What the publisher says
As described on Microsoft Marketplace.
We find the hidden opportunities in your customers’ complaints.
Integrating AI-powered predictive algorithms with human expertise, the PositivityTech Platform uses customer narrative data to break down complaint language, derive variables, and rank risk.
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Click “Contact me” to access PositivityTech’s algorithms and uncover high-risk interactions.
AI Algorithms Key Business Outcomes
· Provide early warnings of customer complaints and illuminate pain points.
· Highlight topics that provide deeper meaning into existing complaints.
· Improve segmentation and offer strategies to get ahead of risks and impact net income.
· Prioritize and adopt actions to inhibit future complaints.
Key Features
The PositivityTech platform’s multiple algorithms reveal potential environmental risks to drive preemptive management actions.
- Severity Score: A proprietary domain-specific algorithm and lexicon that identifies severe complaints and future risk based on customer narratives.
- Sentiment Score: An open-sourced algorithm and lexicon that identifies sentiments expressed in customer narratives.
- Categorization: Consistent and multifaceted grouping of customer complaints provides insights to identify relevant resolutions across all customer touchpoints, from digital to in-person.
- Bias Index: A tool that identifies prejudice within customer complaints and makes it possible to prevent systemic discrimination.
- Using PositivityTech’s AI-powered Bias Index, we’ve explored millions of customer complaints and discovered three types of biases — small in number, yet vital to understand.
- Explicit bias: The customer uses words that indicate they experienced bias.
- Implicit bias: The customer uses contextual references that imply bias.
- Suggested bias: The customer describes situations that hint at bias.
- Triggers: Algorithms that reveal leading indicators of environmental risks, pinpoint timely issues that may require preemptive management actions.
- Debt Collection Model: Predicts the likelihood of non-payment of debts owed.Our algorithms isolate high-risk customer interactions and help you prioritize where business actions will matter most.
Your customer’s voice is your most valuable asset.
Customers tell you what you need to know. Are you listening?
Transform negatives to positives with PositivityTech, and ensure that complaints become a critical part of your success.
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Sources
Publisher resources
11 linksLinked repositories
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