AI-Driven Social Media Personalization & Moderation Platform
AI personalization, real-time moderation, and sentiment analytics for a trust-centered social platform.
Business results:
Compliance is a design constraint we wire in from day one, not a review step before launch — security, privacy, and governance built into every agent.
Customer and employee data protected across every region you operate in.
Security and risk controls, independently audited.
Responsible-AI controls built into every agent — auditable decisions, human-in-the-loop review, and guardrails against bias and data leakage.
Enterprise-grade data management with audit trails, role-based access, and validation engineered into every release rather than bolted on before launch.
Usable by every employee and customer, by design.
Production-grade availability backed by monitoring and SLAs.
Six capability pillars — from feedback ingestion and AI-generated narratives to bias detection and calibration prep.
Ingests every performance signal simultaneously: self-assessments, peer and 360-degree feedback, upward feedback, manager notes, continuous check-in records, and informal feedback from performance platforms.
Generates structured review narratives mapped to your competency framework, review template, and rating scale — not generic summaries requiring complete rewriting.
Scans every review — AI-generated drafts and human edits — for gendered adjectives, attribution asymmetry, doubt-raising language, ability vs. effort framing, and vague praise without evidence.
Generates standardised calibration packs for every manager and department: rating distribution, ranked summaries, evidence quality scores, and peer consistency analysis.
Native connectors for Workday HCM, SAP SuccessFactors, Oracle HCM Cloud, ADP Workforce Now, and BambooHR — bi-directional sync of profiles, templates, feedback, and completed reviews.
Review cycle dashboard: completion rates, time-to-completion, narrative evidence density, bias flag rates, and calibration adjustment magnitude across the organisation.
Every AI agent we build is designed with data protection and security at its core — tailored to your compliance requirements.
Builds a full-period evidence timeline before writing, so Q1 work counts as much as Q4 — no recency bias.
Flags vague praise, doubt-raising language, and other bias patterns before reviews reach the employee.
Standardised AI review packs make every write-up comparable, so calibration stays data-driven at any headcount.
A clear, collaborative AI process — we start with your challenges and goals, then build for real business value.
We start by learning about your business objectives, current systems, and team capabilities. This helps us identify the right opportunities for AI to make a real impact.
Based on what we learn, we create a detailed plan for your AI implementation. This includes technical requirements, timeline, and success metrics.
We develop the AI solution in iterative cycles with regular check-ins. This allows us to adjust based on your feedback and ensure everything works as expected.
We handle the technical deployment and train your team to use the new AI tools effectively. This includes documentation and hands-on support.
After launch, we continue to monitor performance, make improvements, and help you get the most value from your AI investment.
Builds a full-period evidence timeline before writing, so Q1 work counts as much as Q4 — no recency bias.
Flags vague praise, doubt-raising language, and other bias patterns before reviews reach the employee.
Standardised AI review packs make every write-up comparable, so calibration stays data-driven at any headcount.
Six capability pillars — from feedback ingestion and AI-generated narratives to bias detection and calibration prep.
For an enterprise with 500 managers, that's 105,000 hours per year — equivalent to 52 full-time employees writing reviews that are inconsistent, recency-biased, and largely ineffective as development tools.
Get Performance AssessmentThe average manager spends 210 hours per year on performance activities — yet fewer than 30% of companies believe their process delivers value (McKinsey), and only 14% of employees feel their review inspires improvement (Gallup).
Every feedback signal, one evidence timeline.
Evidence-backed drafts in your review template.
Flags biased language before reviews ship.
Standardised calibration packs per manager.
Our Technology
Leveraging cutting-edge frameworks, AI models, and cloud-native tools to build production-grade solutions.
Reliable, compliant telemedicine apps.
AI diagnostics and insights.
Wearables and live dashboards.
Tamper-proof shared records.
HIPAA-compliant and scalable.
Immersive remote diagnostics.
Seamless AI integration for smarter, more efficient, and more secure telemedicine—here's how it works in practice.
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ASSOCHAM Member
Everything CHROs, HR operations leaders, and People Analytics directors need to know about deploying an AI Performance Review Summarizer at enterprise scale.
Talk to an ExpertIt ingests every performance signal — self-assessments, peer feedback, manager notes, check-ins, and goal data — into a structured, evidence-grounded draft the manager refines.
The draft is grounded in specific, attributable evidence, not generic phrases, with each section referencing real events and outcomes.
It applies a research-based taxonomy of evaluation bias — gendered language, attribution asymmetry, doubt-raising phrases, vague praise, and role-incongruent framing.
Native connectors cover Workday HCM, SAP SuccessFactors, Oracle HCM Cloud, ADP Workforce Now, and BambooHR, plus performance platforms (Lattice, Culture Amp, 15Five, Leapsome, Betterworks) and goal tools (Asana, Jira, Monday.com, Ally.io).
360-degree feedback synthesis is a primary use case — the summarizer ingests every reviewer type (self, peers, direct reports, manager, skip-level) with appropriate weighting per source.
The summarizer is cycle-agnostic, generating summaries for any cadence in your HRIS — annual, semi-annual, quarterly, or project-based.
Data is processed under your existing HR vendor agreements — the agent reads and writes via authenticated HRIS APIs, with no data stored in Bonami infrastructure beyond the active session, and role-based access limits managers to their direct reports.
ROI spans three areas: time (a 70% prep-time cut saves 147 manager-hours a year — 73,500 hours for a 500-manager org), talent quality (McKinsey links effective performance management to 24% higher performance and 40% lower attrition), and legal (bias-checked documentation cuts litigation exposure).
Traditional performance appraisal software just gives managers a blank template to fill in from memory. This performance review software does the synthesis — ingesting self-assessments, peer feedback, manager notes, and goal data into a structured, bias-checked draft grounded in attributable evidence from the full review period.
Yes. It functions as performance management software that connects to your existing HRIS and performance platforms rather than replacing them, with 360 feedback software capabilities that synthesize self, peer, upward, and skip-level input, weight each source, and surface conflicts.
Get in touch
Schedule a consultation with our development team to explore your requirements and solution options.