Overview
What is alternative-data synthesis?
Alternative data, satellite imagery, card transactions, job postings, web traffic, supply-chain records, can carry powerful signals, but raw feeds are messy, inconsistent, and easy to misuse without point-in-time discipline.
Alternative-data synthesis builds the pipelines that ingest, clean, normalize, and align these sources, then backtest them against price history so only validated, non-look-ahead signals reach the strategy.
What the system analyzes
The Challenge
Raw alternative data is hard to trust
The value is real, but messy feeds, inconsistent coverage, and look-ahead bias mean most alternative data never becomes a reliable, tradable signal.
Messy, Inconsistent Feeds
Sources vary in format, coverage, and quality.
Entity Mapping
Linking data to the right securities is hard and error-prone.
Look-Ahead Bias
Without point-in-time discipline, backtests lie.
Operational Overhead
Maintaining many feeds is a heavy engineering burden.
Education AI Solutions
How Solnix synthesizes alternative data
Ingestion & Cleaning
Bring messy feeds into a consistent pipeline.
Point-in-Time Normalization
Align data to avoid look-ahead bias.
Entity Mapping
Map data to securities and issuers.
Feature Construction
Build predictive features from raw data.
Backtesting
Validate signals against price history.
Signal Monitoring
Track signal health over time.
End-to-End Implementation
How Solnix implements alt-data synthesis
A phased program from source onboarding through point-in-time normalization and validated backtesting integrated into research workflows.
Discovery & AI Opportunity Mapping
We start by understanding your operations, data landscape, and goals, then map where AI delivers measurable value and where it does not. Every engagement begins with a prioritized opportunity backlog, not a technology pitch.
Data Foundation & Readiness
AI is only as good as the data behind it. We assess data quality, connect fragmented sources, and build the secure, governed pipelines that production AI depends on, with privacy and compliance designed in from the start.
Model & Agent Development
We build the models, retrieval systems, and AI agents tailored to your use cases, selecting the right approach (fine-tuning, RAG, multi-agent orchestration) for accuracy, cost, and latency, and validating against your real-world edge cases.
Integration & Workflow Embedding
AI only creates value when it lives inside the tools your teams already use. We embed models and agents into existing systems, surfaces, and workflows, so adoption is natural and human-in-the-loop controls stay in place.
Deployment, Security & Compliance
We deploy to production with the security, monitoring, and compliance controls enterprises require, including bias and fairness testing, audit logging, and the observability needed to operate AI responsibly at scale.
Optimization & Continuous Improvement
AI systems improve with use. We measure outcomes against the goals set in Phase 01, retrain and tune from live feedback, and expand to the next set of use cases, turning a single deployment into a compounding capability.
Key Capabilities
Key capabilities
Robust Ingestion
Handle diverse feeds.
Benefits
Point-in-Time Discipline
Prevent look-ahead.
Benefits
Entity Resolution
Map to securities.
Benefits
Feature Engineering
Build predictive features.
Benefits
Backtesting
Validate rigorously.
Benefits
Signal Monitoring
Watch decay.
Benefits
Who Benefits
Outcomes for data teams, quants, and the desk
For Data Teams
Less plumbing, more signal.
For Quants
Validated, ready features.
For the Desk
Unique, durable edge.
Education Segments
Explore related capital-markets AI
Algorithmic Trade Intelligence
Turn alt-data features into trade signals.
Market Sentiment Intelligence
Blend with sentiment signals.
Earnings Call NLP
Add call-derived signals.
Portfolio Attribution AI
Attribute returns to signals.
Enterprise Automation
Automate data operations.
Agent Ecosystem
Orchestrate data pipelines.
Methodology
How Solnix builds for capital markets
01, Trading & Risk Workflow Assessment
01, Trading & Risk Workflow Assessment
We map your desk, risk, and compliance workflows to target the AI interventions with the clearest measurable edge.
02, Market-Data & Model Architecture
02, Market-Data & Model Architecture
We build governed pipelines over market, reference, and alternative data with the latency and lineage trading and risk demand.
03, Model Validation & Backtesting
03, Model Validation & Backtesting
Every model is backtested and independently validated against historical regimes before it informs a decision.
04, Compliance & Audit by Design
04, Compliance & Audit by Design
Explainability, audit trails, and model-risk-management alignment (SR 11-7) are built in, not bolted on.
05, Continuous Monitoring
05, Continuous Monitoring
Live monitoring tracks model performance and drift across regimes, triggering revalidation as markets change.
FAQ
Questions from data and quant leaders
Get Started
Make Alt-Data Actually Tradable.
Talk to a Solnix alt-data specialist about building validated, point-in-time signal pipelines from your sources.
Talk to an Alt-Data Specialist →