Signal generation
NLP sentiment, event detection, and factor models with documented feature pipelines.
Industry · Capital markets
AI for capital markets
We build AI for asset managers and research desks — multi-agent equity research, NLP sentiment signals, ranking models, event-driven alerts, and backtesting pipelines with explainability and audit trails for regulated environments.
+12%Backtest alpha
847Tickers tracked
Multi-agentResearch
ExplainableSignals
Industry context
Research AI with rigor
Capital markets AI demands reproducible signals, explainable features, and governance for model risk. We combine NLP on filings and news, structured alternative data, and agent workflows that accelerate research without black-box decisions.
Multi-agent research
Agents for summarization, comparison, hypothesis testing, and report drafting.
Backtesting discipline
Walk-forward validation, transaction costs, and reproducible experiment tracking.
Governance ready
Model documentation, bias monitoring, and audit trails for compliance teams.
Use cases
Where markets AI delivers
Use cases for research, portfolio, and risk teams.
Equity Research Agents
Multi-agent workflows for earnings analysis, peer comparison, and draft research notes with source citations.
- Filings + news
- Agent orchestration
- Citation binding
NLP Signal Pipelines
FinBERT and custom transformers for sentiment, topic shifts, and event detection across corpora.
- Real-time ingest
- Entity linking
- Signal stores
Ranking Models
LightGBM and ensemble rankers for idea generation with SHAP explainability and drift monitoring.
- Feature stores
- Walk-forward
- Risk overlays
Portfolio Monitoring
Alerting on factor exposure, concentration, and macro regime shifts with natural language summaries.
- Dashboards
- Slack/email alerts
- What-changed digests
Backtesting Platforms
Reproducible backtests with costs, slippage assumptions, and experiment versioning.
- MLflow tracking
- Report export
- Compliance logs
Analyst Copilots
In-desk assistants for document Q&A, chart explanation, and meeting prep over internal research.
- RAG over notes
- Tool use
- Access controls
Proof of work
Markets delivery
Agent and ML systems with measurable research velocity and signal quality.
Multi-Agent Research Platform
Agent workflows for scoring, summarization, and pipeline analytics — applicable to research desk automation.
47%More conversions
3.2xAnalyst productivity
Real-Time Scoring Engine
Sub-100ms ensemble scoring at millions of events/day — architecture transferable to market signal serving.
47msLatency
68%Detection lift
Regulatory RAG System
Document intelligence over regulatory and policy corpora with audit-ready retrieval.
78%Faster review
$900KAnnual savings
How we help
Related services
Production AI capabilities we bring to every industry engagement.
01Can AI improve equity research productivity?
Yes — agents automate summarization, peer comparison, and first-draft notes while analysts focus on judgment calls. Teams typically see 2–3x throughput on coverage tasks.
02How do you validate trading and ranking signals?
Walk-forward backtests, out-of-sample holds, transaction cost modeling, and reproducible experiment tracking with documented features.
03Do you support explainability for regulators?
SHAP and feature attribution, model cards, drift monitoring, and audit logs for signal generation and overrides.
04What data sources can you integrate?
SEC filings, earnings transcripts, news feeds, alternative data vendors, internal research, and portfolio systems via API.
Next step
Ready to build markets AI?
Tell us about your research stack — we'll design explainable signals and agent workflows with proper governance.