Real-Time Agents for Complex Workflows
Real time signals, shifting conditions, and long chains of decisions slow complex workflows. WalkingTree Technologies agents watch the data, understand the situation, choose the next step, and complete the action so your processes keep moving without stalls.
Agents That Analyze, Decide, and Get Work Done
Stop just automating tasks – delegate entire outcomes. WalkingTree’s autonomous agents act as a true digital workforce. They don’t just do; they analyze complex scenarios, decide on the best path forward, and act independently across your entire operation.
Move at Scale
Empower your teams to execute complex workflows - from market analysis to logistics - in minutes, not days.
Decide with Clarity
Make critical, data-driven calls with less effort and more confidence.
Reduce Risk
Let agents proactively identify, flag, and resolve issues 24/7 before they impact your bottom line.
Explore the Agents Behind the Automation
Discovery & Sourcing
High Growth Scouting Agent
This agent detects high growth potential companies by evaluating revenue momentum, innovation signals and market expansion patterns.
Features
- The agent scans earnings reports, investor presentations and market datasets to identify early growth indicators.
- It analyzes revenue acceleration, margin expansion and innovation intensity using AI driven reasoning.
- It validates growth signals through collaboration with macro agents to confirm sector level tailwinds.
Advantages
- Identifies promising companies before they appear on mainstream radars.
- Reduces noise with sector aligned verification of growth signals.
- Improves detection accuracy using feedback from prior recommendations
Use Cases
- Build early stage growth watchlists.
- Spot firms expanding into new products or regions.
- Identify companies with strengthening fundamentals.
Earning Surprise & Anomaly Detection Agent
This agent detects earnings surprises and anomalies by comparing forecasts with reported results and interpreting management commentary.
Features
- The agent compares analyst consensus data against reported earnings to identify significant deviations.
- It uses natural language analysis to interpret management remarks for context behind the numbers.
- It sends anomaly alerts to the Portfolio Manager Agent when deviations may indicate actionable opportunities.
Advantages
- Highlights earnings events that are likely to drive price movement.
- Reduces noise by filtering out low impact deviations.
- Improves reliability with continuous threshold calibration.
Use Cases
- Flag companies with unexpected margin or revenue changes.
- Identify high impact earnings beats or misses.
- Track recurring reporting irregularities.
Insider Activity Monitoring Agent
This agent analyzes insider trading behavior to reveal leadership sentiment and identify early confidence or caution signals.
Features
- The agent monitors insider trade disclosures and filings to detect unusual buying or selling activity.
- It evaluates trade context such as timing, size and price range to distinguish meaningful patterns.
- It collaborates with risk agents to validate compliance context while building long term insider behavior profiles.
Advantages
- Shows early indicators of management conviction or concern.
- Filters out routine or automated transaction noise.
- Strengthens sentiment analysis through historical pattern tracking.
Use Cases
- Catch leadership confidence improving before earnings.
- Flag abnormal selling behavior in stable companies.
- Track evolving insider sentiment across quarters.
Institutional Flow Detection Agent
This agent identifies institutional inflows and outflows by analyzing fund holdings, block trades and trading patterns across major institutions.
Features
- The agent monitors 13F filings, holdings disclosures and large block trades to detect institutional positioning changes.
- It distinguishes conviction trades from passive rebalancing using reasoning based on context and timing.
- It updates institutional sentiment scores using memory to strengthen trend detection.
Advantages
- Reveals sustained buying or selling pressure from large investors.
- Helps separate structural flows from conviction driven moves.
- Provides a clearer view of institutional sentiment across sectors.
Use Cases
- Spot companies gaining consistent institutional support.
- Detect broad selling pressure across funds during rotations.
- Identify conviction trades that may not be obvious in price action.
Mutual Fund Portfolio Monitoring Agents
This agent analyzes mutual fund portfolio changes to reveal positioning shifts, concentration risks and evolving market themes.
Features
- The agent extracts and compares mutual fund holdings to identify trims, additions and rebalancing patterns.
- It measures overlap and concentration across funds using similarity search to detect crowding risks.
- It stores multi period positioning data to highlight long term shifts in consensus.
Advantages
- Surfaces emerging themes gaining traction across major funds.
- Flags early exits from crowded or overexposed positions.
- Helps identify rising concentration that could increase portfolio risk.
Use Cases
- Track sector or thematic trends across mutual funds.
- Detect early selling in high ownership names.
- Identify concentration risks within fund clusters.
Fundamental & Technical Analysis
Fundamental and Value Analyst
This agent evaluates intrinsic value by analyzing financial statements, normalized models, sector context and valuation frameworks.
Features
- The agent ingests filings, guidance and broker models to build normalized financial statements for each company.
- It applies valuation methods such as DCF, comparables and quality scoring using structured financial data.
- It coordinates with macro and sector agents to adjust fair value estimates for changing market regimes.
Advantages
- Produces consistent and transparent intrinsic value estimates.
- Adapts valuations to macro and sector shifts for higher relevance.
- Detects valuation drift using historical outcomes stored in memory.
Use Cases
- Identify undervalued companies with improving fundamentals.
- Flag names trading above reasonable valuation ranges.
- Support portfolio decisions with margin of safety insights.
Technical Timing Analyst
This agent identifies optimal entry and exit points by analyzing price trends, volume activity and multi horizon technical signals.
Features
- The agent streams OHLCV, options and order book data to generate multi timeframe technical signals.
- It uses backtesting tools to evaluate signal performance and refine thresholds based on historical behavior.
- It adjusts signal sensitivity using reinforcement learning informed by slippage and execution outcomes.
Advantages
- Helps traders act on clean breakout or timing setups.
- Learns from execution results to improve future signals.
- Aligns timing recommendations with market liquidity conditions.
Use Cases
- Identify clean breakout opportunities.
- Flag volatility compression setups before directional moves.
- Provide precise entry and exit levels.
Mean Reversion Signal
This agent identifies potential mean reversion trades by detecting stretched price moves across statistical and momentum indicators.
Features
- The agent calculates z scores, moving average deviations and momentum extremes to identify stretched conditions.
- It cross checks potential reversion signals against event calendars to reduce false positives during volatile periods.
- It can automatically generate reversion candidate baskets by combining reliability scores and event risk filters.
Advantages
- Improves detection of short lived reversion opportunities.
- Reduces noise by accounting for event driven distortions.
- Strengthens conviction with ticker specific reliability data.
Use Cases
- Identify oversold names after temporary declines.
- Detects overbought conditions likely to revert.
- Build reversion baskets with predefined targets.
Style Factor Exposure
This agent analyzes portfolio exposure to value, growth, momentum, size and quality factors to explain risk and performance patterns.
Features
- The agent computes factor exposures using cross sectional regressions across multiple style dimensions.
- It tracks rolling factor betas to reveal changing exposure patterns over time.
- It coordinates with diversification agents to suggest factor corrections.
Advantages
- Reveals hidden factor tilts influencing portfolio behavior.
- Helps manage unintended style risks.
- Explains performance trends through structured factor attribution.
Use Cases
- Identify unintended style exposures driving volatility.
- Recommend hedges for concentrated factor risk.
- Clarify recent portfolio performance using factor attribution.
Macro & Sentiment Intelligence
Macro & Cyclicality Analyst
This agent identifies market phases and macro trends by analyzing economic indicators and mapping their impact on sectors and equities.
Features
- The agent pulls macroeconomic data such as GDP, inflation, rates and PMI to assess current economic conditions.
- It uses AI reasoning to map macro indicators to market phases and infer likely sector behavior.
- It adapts its models using reinforcement feedback from portfolio performance during different regimes.
Advantages
- Helps recognize transitions between economic cycles early.
- Improves sector allocation decisions with macro aligned insights.
- Enhances reliability by learning from past market outcomes.
Use Cases
- Track shifts from expansion to contraction or stagnation.
- Identify sectors favored by current macro trends.
- Adjust portfolio exposure during rate or inflation changes.
News and Sentiment Analyst
This agent derives actionable sentiment insights by analyzing real time news, social signals and context relevant market commentary.
Features
- The agent uses language models with retrieval from financial news feeds and social sources to interpret sentiment.
- It filters noise by ranking updates based on impact, relevance and polarity.
- It clusters topics and stores sentiment trendlines in memory for each company over time.
Advantages
- Provides early visibility into sentiment reversals or emerging themes.
- Reduces noise by ignoring low relevance updates.
- Supports long term decisions with structured sentiment history.
Use Cases
- Track shifts in sentiment for key holdings.
- Identify themes gaining market attention.
- Monitor negative sentiment buildup before it reflects in price.
Lead-Lag Sector Rotation Analyst
This agent predicts sector rotations by analyzing leadership patterns, inter sector correlations and macro aligned performance signals.
Features
- The agent monitors sector level performance spreads and correlation shifts to detect changing leadership.
- It learns cyclical rotation behaviors such as moves between defensive and cyclical sectors.
- It validates rotation signals by coordinating with macro analysts for contextual confirmation.
Advantages
- Helps identify early sector leadership changes.
- Supports allocation decisions with cycle aware insights.
- Improves rotation timing by combining pattern and macro signals.
Use Cases
- Detect weakening leadership before a rotation occurs.
- Identify moves into defensive or cyclical sectors.
- Guide allocation changes based on confirmed rotation signals.
Analyst Consensus Drift Analyst
This agent tracks shifts in analyst forecasts and target prices to reveal changing expectations and sentiment direction.
Features
- The agent monitors broker updates and consensus data feeds to detect forecast changes.
- It analyzes whether revisions are reactive or anticipatory using chain of thought reasoning.
- It stores long term sentiment bias patterns in memory for future reference.
Advantages
- Highlights meaningful estimate trends that influence price behavior.
- Distinguishes noise from revisions that matter.
- Improves conviction by revealing sustained analyst directionality.
Use Cases
- Identify stocks with consistent upgrades or downgrades.
- Flag sectors undergoing broad estimate revisions.
- Track early shifts in analyst sentiment.
Retail Sentiment Analyzer
This agent measures retail investor sentiment by analyzing social activity, trading signals and behavior patterns across crowd driven platforms.
Features
- The agent collects data from forums, social platforms and retail focused sentiment sources.
- It detects hype clusters or fear driven spikes using embedding based similarity patterns.
- It compares retail sentiment with institutional behavior to identify divergences.
Advantages
- Helps identify crowd driven surges that may not reflect fundamentals.
- Reveals divergences between retail and institutional signals.
- Tracks long term sentiment patterns to adjust confidence levels.
Use Cases
- Detect retail driven momentum spikes.
- Identify panic selling opportunities.
- Spot divergence between institutional flows and retail attention.
Strategy Synthesis & Governance
Portfolio Manager (Decision Synthesis)
This agent synthesizes signals from fundamental, technical, macro and sentiment agents to deliver clear portfolio decisions.
Features
- The agent gathers insights from analysis agents to create a unified understanding of each investment situation.
- It uses reasoning to reconcile conflicting signals and form a balanced buy, hold or sell recommendation.
- It adapts signal weighting using reinforcement learning based on historical performance and realized outcomes.
Advantages
- Provides a centralized decision layer that reduces noise from multiple agents.
- Improves the consistency of portfolio decisions with structured reasoning.
- Learns from past trades to enhance future positioning accuracy.
Use Cases
- Produce final buy, hold or sell recommendations.
- Manage dynamic portfolio rebalancing.
- Align signals from multiple analysis agents.
CEO/CXO Confidence Signal Agent
This agent analyzes leadership communication to detect shifts in executive confidence, tone and clarity that influence conviction.
Features
- The agent evaluates earnings transcripts, press releases and interviews to interpret management tone and sentiment.
- It uses semantic and tonal analysis to detect optimism, caution or defensiveness in executive communication.
- It generates a confidence index and updates it over time based on ongoing leadership commentary.
Advantages
- Helps identify subtle shifts in leadership confidence before they appear in performance.
- Enhances conviction scoring for portfolio decisions.
- Supports deeper understanding of management reliability and intent.
Use Cases
- Monitor rising or falling leadership confidence.
- Detect early caution before guidance changes.
- Strengthen conviction assessments during investment reviews.
Trade Rationale Auditor
This agent ensures transparency by tracing every trade decision back to the signals, logic and data that influenced it.
Features
- The agent records which analytical agents and signals contributed to each trade decision.
- It detects inconsistencies or potential overfitting in decision logic by analyzing deviations between expected and realized outcomes.
- It generates clear and human readable trade summaries for governance and audit teams.
Advantages
- Improves accountability and clarity across investment decisions.
- Identifies weaknesses in trade logic and supports continuous refinement.
- Strengthens compliance and governance processes.
Use Cases
- Provide audit ready rationale for every executed trade.
- Detect inconsistencies in decision making.
- Support compliance and policy reviews.
Red-Team Agent
This agent challenges investment decisions by generating adversarial scenarios that test assumptions, risks and portfolio resilience.
Features
- The agent examines trade recommendations and questions key assumptions using targeted adversarial reasoning.
- It runs scenario simulations to evaluate how recommendations perform under varied macro or market conditions.
- It shares its findings with the Portfolio Manager and Risk Management agents for final review.
Advantages
- Helps uncover blind spots in high conviction positions.
- Strengthens the robustness of investment decisions.
- Enhances risk preparedness through structured scenario testing.
Use Cases
- Stress test trades under adverse macro conditions.
- Evaluate downside risks before execution.
- Test portfolio resilience across unexpected scenarios.
Risk & Compliance
Risk Management Agent
This agent monitors portfolio risk by tracking volatility, drawdowns and correlation patterns to identify emerging exposures.
Features
- The agent evaluates position level and portfolio level risk using live and historical volatility, drawdown and correlation data.
- It identifies concentration and regime risks by analyzing clustering patterns across sectors or factors.
- It recommends hedges or position adjustments by coordinating with related decision and execution agents.
Advantages
- Helps prevent unnoticed buildup of risk in portfolios.
- Enhances resilience by detecting early signs of stress.
- Supports disciplined portfolio adjustments during market shifts.
Use Cases
- Flag concentration in specific sectors or themes.
- Detect rising volatility that could threaten holdings.
- Recommend hedges during unstable market periods.
Compliance Assurance Agent
This agent enforces compliance by checking every trade against regulatory rules, internal policies and approved data sources.
Features
- The agent validates trades against regulatory limits, internal rules and ethical policies before they proceed.
- It scans decision logs to detect use of unapproved data sources or potential policy violations.
- It flags or halts trades that show signs of restricted activity or governance risk.
Advantages
- Prevents breaches of regulatory or internal guidelines.
- Reduces operational and reputational risk.
- Strengthens trust and audit readiness through continuous oversight.
Use Cases
- Prevent trades that exceed position or exposure limits.
- Detect possible insider linked activity.
- Monitor adherence to approved data and model usage.
Black Swan Sentinel Agent
This agent detects rare and high impact events by monitoring long tail signals, global disruptions and early warning indicators.
Features
- The agent uses anomaly detection to identify unusual macro, geopolitical or market activity.
- It monitors global news and long horizon indicators that may signal extreme risk events.
- It triggers targeted stress tests across portfolios to show potential impact zones.
Advantages
- Provides early alerts on shocks that standard models often miss.
- Helps prepare portfolios for extreme volatility.
- Improves risk preparedness through scenario awareness.
Use Cases
- Alert on sudden commodity or currency spikes.
- Run stress tests after major geopolitical events.
- Detect rare risks that may not appear in baseline models.
Bias and Fairness Monitoring Agent
This agent detects bias in data, models and reasoning patterns to ensure balanced and consistent decision making across agents.
Features
- The agent monitors decision logs for recency bias, source bias and skewed reasoning patterns.
- It tests model behavior using historical comparisons to identify signs of overfitting or uneven outcomes.
- It adjusts reasoning logic by updating prompts or parameters to improve fairness.
Advantages
- Reduces hidden biases that affect portfolio decisions.
- Improves consistency of analytical insights.
- Helps maintain transparency and trust across AI workflows.
Use Cases
- Flag bias in recurring recommendations.
- Diagnose overfitting in signals or reasoning.
- Improve fairness across varying market conditions.
Alternative Regime Hypothesis Agent
This agent identifies shifts in market regimes by analyzing macro financial transitions and testing assumptions under new scenarios.
Features
- The agent learns market regime patterns using clustering techniques across macro and financial variables.
- It tests existing model assumptions under alternative scenarios generated through synthetic simulation.
- It signals dependent agents when recalibration is required due to a potential regime shift.
Advantages
- Helps detect early signs of new market environments.
- Ensures models remain aligned with evolving conditions.
- Strengthens risk and decision processes through proactive recalibration.
Use Cases
- Detect high volatility periods early.
- Flag transitions into bull or bear phases.
- Trigger recalibration across connected agents.
Execution & Feedback
Liquidity & Impact Agent
This agent evaluates trade feasibility by analyzing liquidity depth, spreads and potential market impact before execution.
Features
- The agent tracks liquidity levels, spreads and volatility using order book and tick data.
- It estimates expected slippage and price impact based on historical transaction behavior.
- It recommends execution windows and order slicing strategies by coordinating with related agents.
Advantages
- Helps avoid trades that may cause excessive market impact.
- Improves execution quality through informed timing.
- Supports traders with practical guidance on order sizing.
Use Cases
- Identify the best time to execute large orders.
- Flag illiquid positions with high expected slippage.
- Recommend slicing approaches to reduce impact.
Execution Feedback & Slippage Agent
This agent monitors trade execution quality by comparing achieved prices with expected fills to refine future execution models.
Features
- The agent captures executed trade data and measures deviation between expected and realized fill prices.
- It evaluates broker and venue performance using historical slippage and fill pattern analysis.
- It updates execution assumptions and provides feedback to decision and liquidity agents.
Advantages
- Improves future execution accuracy through continuous learning.
- Highlights brokers or venues that consistently underperform.
- Helps refine trading strategies for different market conditions.
Use Cases
- Detect brokers with persistent slippage issues.
- Identify time of day patterns affecting execution.
- Tune execution models based on real outcomes.
Microstructure Awareness Agent
This agent analyzes short term price movements and order book behavior to guide execution decisions and detect hidden market activity.
Features
- The agent monitors order book shifts, quote imbalances and liquidity changes across intraday intervals.
- It identifies hidden liquidity, spoofing patterns and micro level pressures using event driven analysis.
- It recommends suitable order types by evaluating current microstructure conditions.
Advantages
- Helps avoid adverse selection by detecting short term pressures.
- Improves execution precision in fast moving markets.
- Reveals hidden liquidity conditions that impact order strategy.
Use Cases
- Spot stealth buying or selling pressure.
- Adjust order types during microstructure shifts.
- Improve fill quality through intraday insight.
Performance & Learning Analyst Agent
This agent analyzes performance drivers by consolidating signals, trades and outcomes to improve future agent behavior.
Features
- The agent aggregates data from signals, trades and risk logs to perform performance attribution.
- It identifies alpha sources, signal decay and execution impacts by analyzing historical outcomes.
- It shares improvement suggestions with dependent agents through the knowledge memory system.
Advantages
- Strengthens model performance through structured learning.
- Reveals which signals consistently add or reduce value.
- Supports continuous refinement across the multi agent system.
Use Cases
- Identify underperforming strategies for review.
- Track the reliability of different signal types.
- Improve agent behavior using attribution insights.
Meta & Orchestration
Knowledge Memory Agent
This agent acts as a shared memory system that stores insights, reasoning traces and historical data for all other agents.
Features
- The agent collects structured outputs, reasoning steps and outcomes from analytical and operational agents.
- It uses embeddings and vector search to recall relevant past scenarios or insights for current tasks.
- It supports long and short term memory retrieval to help agents operate with shared context.
Advantages
- Improves reasoning quality across agents through shared memory.
- Reduces repeated work by recalling similar past analyses.
- Strengthens decision making with context aware retrieval.
Use Cases
- Retrieve insights from similar past market regimes.
- Link previous analysis to current decisions.
- Support cross agent reasoning with consistent historical context.
Prompt & Strategy Tuner Agent
This agent improves performance by fine tuning prompts, reasoning strategies and tool choices based on how other agents behave.
Features
- The agent observes performance metrics and outcomes from agents to adjust prompts and reasoning patterns.
- It uses reinforcement learning signals to refine instructions for different document types or market conditions.
- It updates tool usage patterns to increase efficiency and accuracy across changing scenarios.
Advantages
- Enhances accuracy by keeping prompts aligned with real performance.
- Reduces unnecessary computation from poorly tuned strategies.
- Improves adaptability during shifts in market or input complexity.
Use Cases
- Improve extraction quality for complex filings.
- Reduce unnecessary tool calls.
- Adapt reasoning during volatile markets.
Meta-Coordinator Agent
This agent orchestrates workflows by deciding which agents to activate, how to sequence them and how to resolve conflicting outputs.
Features
- The agent uses dynamic planning logic to determine the optimal set of agents for each analytical or operational task.
- It resolves conflicting outputs through weighted aggregation based on confidence and relevance.
- It coordinates multi step workflows by sequencing agents to achieve efficient execution.
Advantages
- Ensures cooperative behavior across the entire agent ecosystem.
- Reduces conflicts between analytical signals.
- Improves workflow efficiency through intelligent orchestration.
Use Cases
- Manage workflows during earnings season.
- Resolve conflicting buy or sell signals.
- Coordinate multi step analysis processes.
Other Specialized Agents
Earnings Call Q&A Deep Read Agent
This agent analyzes Q&A transcripts to extract tone, intent and key insights from management responses across earnings calls.
Features
- The agent uses language models to interpret Q&A conversations and extract tone, polarity and clarity indicators.
- It identifies recurring concerns or themes raised by analysts during the Q&A segment.
- It links Q&A commentary to financial performance metrics and stores insights for trend tracking.
Advantages
- Highlights subtle signals in leadership communication.
- Reveals recurring concerns that may affect future performance.
- Strengthens analysis with structured transcript insights.
Use Cases
- Detect changes in management tone.
- Track evolving investor concerns.
- Support conviction scoring with deeper transcript context.
Cross-Listed & ADR Arbitrage Agent
This agent identifies price gaps between domestic and ADR listings by analyzing currency adjusted spreads and parity deviations.
Features
- The agent monitors price movements across domestic and ADR markets to identify parity inconsistencies.
- It calculates currency adjusted spreads and checks whether these spreads exceed execution costs.
- It flags recurring or persistent gaps that may offer arbitrage opportunities.
Advantages
- Reveals pricing inefficiencies that standard screens miss.
- Helps identify low risk relative value trades.
- Improves timing by detecting persistent spread patterns.
Use Cases
- Flag ADRs trading at premiums or discounts.
- Detect parity gaps after currency movements.
- Track repeating arbitrage opportunities.
Regulatory Horizon Scanner Agent
This agent tracks regulatory changes by analyzing policy updates, sector specific rules and compliance frameworks to identify upcoming impacts.
Features
- The agent parses government releases, exchange notices and policy drafts using retrieval and reasoning.
- It classifies updates by urgency, relevance and sector impact, and maps regulatory changes to affected sectors.
- It alerts compliance and risk agents when new obligations or opportunities emerge.
Advantages
- Helps teams stay ahead of upcoming regulatory shifts.
- Reduces compliance risk through early awareness.
- Supports planning with clear impact categorization.
Use Cases
- Identify regulatory changes affecting holdings.
- Flag new compliance obligations early.
- Monitor evolving ESG or tax standards.
IPO Opportunity Screener Agent
This agent evaluates upcoming IPOs by analyzing fundamentals, sector alignment and subscription momentum to assess listing potential.
Features
- The agent reviews pre listing documents, financials and peer comparisons to evaluate company strength.
- It monitors subscription trends and sentiment signals to estimate demand.
- It predicts possible listing outcomes using structured analysis and pattern matching.
Advantages
- Helps rank IPOs by expected strength and attractiveness.
- Flags overpriced or underpriced offerings early.
- Improves preparation for upcoming listing events.
Use Cases
- Evaluate the quality of upcoming IPOs.
- Detect strong early subscription momentum.
- Flag potential mispricing relative to peers.
Reverse DCF Assumption Auditor Agent
This agent uncovers the growth and margin expectations implied by current stock prices through reverse engineered valuation analysis.
Features
- The agent performs reverse DCF calculations to determine implicit growth or margin assumptions.
- It compares these assumptions with historical performance and sector norms to test realism.
- It sends insights to valuation agents for integration into broader models.
Advantages
- Helps validate valuation assumptions with transparent math.
- Flags unrealistic growth expectations embedded in prices.
- Supports fair value models with grounded inputs.
Use Cases
- Identify companies priced for unrealistic growth.
- Validate inputs in valuation models.
- Compare implied assumptions with sector benchmarks.
Portfolio Diversification Optimizer Agent
This agent recommends diversification strategies by analyzing correlations, concentration risks and portfolio level exposures.
Features
- The agent evaluates covariance matrices and factor correlations to identify concentration and tail risks.
- It simulates alternative portfolio structures to map efficiency improvements.
- It collaborates with risk and factor agents to recommend diversification adjustments.
Advantages
- Improves portfolio resilience with balanced exposure.
- Helps reduce unintended concentration risks.
- Supports more efficient allocation decisions.
Use Cases
- Reduce concentration in crowded themes.
- Improve diversification across sectors or factors.
- Strengthen resilience during volatile periods.
Counter-Trend Macro Predictor Agent
This agent detects macro divergences by identifying mismatches between economic fundamentals and prevailing market pricing.
Features
- The agent monitors macro indicators and compares them with market pricing to detect divergences.
- It uses reasoning to identify overreactions or delays in market response.
- It generates contrarian scenarios for review by portfolio decision agents.
Advantages
- Helps identify overlooked macro opportunities.
- Highlights sentiment driven mispricing.
- Supports contrarian positioning with grounded logic.
Use Cases
- Spot sectors priced too pessimistically.
- Detect markets slow to reflect improving fundamentals.
- Surface contrarian trades during extreme sentiment.
Market Micro-Narratives Cluster Agent
This agent clusters emerging market narratives by analyzing news, social signals and sector commentary to reveal evolving themes.
Features
- The agent ingests articles, transcripts and social data to identify narrative patterns.
- It uses embedding based clustering to group related news and sentiment themes.
- It updates narrative graphs to show how themes influence sectors or stocks over time.
Advantages
- Provides visibility into fast moving market narratives.
- Helps identify themes gaining or losing momentum.
- Supports early trend discovery through narrative tracking.
Use Cases
- Identify rising themes influencing investor behavior.
- Track shifts in dominant narratives.
- Link narrative changes to sector opportunities.
Cross-Functional Enterprise Agents
Aspira - Interview Agent
This agent conducts structured voice or chat interviews by capturing responses, evaluating them against predefined criteria, and delivering clear summaries for HR teams.
Features
- Runs interviews or surveys through voice or chat with consistent question flows
- Analyzes responses for clarity, relevance, and skill alignment
- Generates transcripts and structured evaluation summaries
- Connects with recruitment or workflow systems for smooth shortlisting
Advantages
-
- Reduces early stage HR workload
- Improves consistency across evaluations
Handles large applicant or participant volumes without delays
Use Cases
- Automate first round interviews
- Screen applicants during high volume hiring
- Collect structured feedback or survey responses
- Support multilingual or remote-first screening
Intellexi - Document Ingestion Agent
This agent extracts key information from unstructured documents by reading, structuring, and organizing data so teams can search and act on it easily.
Features
- Reads PDFs, scanned forms, images, and handwritten notes
- Extracts key fields, text blocks, and domain-relevant details
- Summarizes and compares data across related documents
- Creates a searchable knowledge layer for quick information retrieval
Advantages
- Speeds up document-heavy processes
- Reduces manual data extraction and errors
- Makes important information easy to find and reuse
Use Cases
- Process claims, applications, or compliance files
- Summarize long policy or contract documents
- Search across large sets of institutional or business documents
- Support admissions, audit, and operational workflows
Educhestra - Edutech Agent
This agent provides accurate answers, adaptive tutoring, and 24/7 support across all channels, while centralizing student interactions and simplifying admissions.
Features
- Provides academic guidance, tutoring help, and campus information across channels
- Reads marksheets and documents to generate personalized course and university suggestions
- Tracks application status and automates reminders, follow-ups, and notifications
- Syncs all chats, calls, and updates into a unified CRM for full visibility
Advantages
- Cuts response times and reduces manual effort for admissions teams
- Keeps communication consistent across languages, regions, and channels
- Handles large query and applicant volumes without delays
- Improves engagement and conversion with personalized recommendations
Use Cases
- Automate admissions FAQs, status checks, and document reminders
- Guide students through course and university selection based on academic profiles
- Act as a 24/7 campus concierge for academic, administrative, and general support
- Help agents and counselors manage applications and follow-ups in one system
Sales Einstein - Sales Agent
This agent boosts sales performance by joining live calls, giving real-time guidance, and turning every conversation into clear insights your team can use to close more deals.
Features
- Joins calls and suggests counterpoints, comparisons, and use cases
- Analyzes conversations for intent, objections, and decision cues
- Generates post-call summaries, scorecards, and coaching insights
- Connects with CRMs, call tools, and product catalogs
Advantages
- Reduces manual coaching time across the team
- Unlocks insights hidden in unreviewed call data
- Keeps pitches consistent and aligned with your playbooks
- Helps reps personalize conversations quickly and confidently
Use Cases
- Guide live demos with real-time prompts and objection handling
- Improve win rates using data-backed conversation analysis
- Speed up onboarding with structured feedback and call summaries
- Support sales cycles across SaaS, BFSI, healthcare, and more
AuditPro - Audit Agent
This agent turns compliance documents into executable rules and validates them directly on real data. It automates the full audit cycle and delivers clear, actionable reports.
Features
- Extracts audit rules, clauses, and conditions from uploaded compliance documents
- Reads database metadata and maps rules to tables, fields, and constraints
- Generates native SQL or NoSQL scripts and executes them securely via MCP
- Produces full audit reports with compliance percentages and rule-level results
Advantages
- Removes manual effort from early audit stages
- Delivers consistent, repeatable rule validation
- Scales across domains, data sources, and project volumes
- Gives clear insight into strengths, gaps, and non-compliance areas
Use Cases
- Automate recurring compliance audits across departments
- Validate policies against real operational data
- Run scheduled audit cycles without manual execution
- Support internal, external, and regulatory audit requirements
Code Canopy - Coding Agent
This agent analyzes codebases and documents to surface logic, structure, and dependencies. It then generates SDLC artifacts teams can use across engineering, QA, and architecture.
Features
- Reads repositories across languages and extracts business logic, flows, and patterns
- Processes PDFs, docs, and code files to unify technical and non-technical knowledge
- Generates specs, test plans, architecture docs, and semantic search embeddings
- Runs multi-agent workflows for structure mapping, dependency review, and security checks
Advantages
- Cuts down manual analysis and documentation time
- Makes legacy and complex codebases easier to understand
- Keeps knowledge searchable, reusable, and always up to date
- Covers the full SDLC from requirements to architecture and QA
Use Cases
- Reverse-engineer and document existing or legacy systems
- Produce SDLC artifacts automatically for new or evolving projects
- Assess impact of code changes and dependencies
- Build searchable technical knowledge bases for faster onboarding
Recruitment Agent
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Features
- The agent collects data from forums, social platforms and retail focused sentiment sources.
- It detects hype clusters or fear driven spikes using embedding based similarity patterns.
- It compares retail sentiment with institutional behavior to identify divergences.
Advantages
- Helps identify crowd driven surges that may not reflect fundamentals.
- Reveals divergences between retail and institutional signals.
- Tracks long term sentiment patterns to adjust confidence levels.
Use Cases
- Detect retail driven momentum spikes.
- Identify panic selling opportunities.
- Spot divergence between institutional flows and retail attention.