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Kensho

  • What it is:Kensho is the AI Innovation Hub for S&P Global that develops machine learning solutions to structure unstructured data like text and speech into actionable business insights.
  • Best for:Large investment banks and hedge funds, Quant teams and risk managers, Equity analysts and investment bankers
  • Pricing:Starting from Starting at $10,000/month
  • Rating:92/100Excellent
  • Expert's conclusion:Kensho is great for large financial services firms that can use S&P Global Data; however, it represents premium enterprise software and cannot be used by small companies.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Kensho and What Does It Do?

Kensho is an AI firm that specializes in machine intelligence for financial analytics, socio-economic analysis, and national security applications. Kensho was formed from research at Harvard and MIT. Kensho allows users to query complex data sets using their own words for quick insight. Kensho was purchased by S&P Global in 2018 for $550 million dollars and is still based in Cambridge Massachusetts.

Active
📍Cambridge, MA
📅Founded 2013
🏢Subsidiary
TARGET SEGMENTS
Financial InstitutionsWall StreetNational SecurityGovernment

What Are Kensho's Key Business Metrics?

📊
$72.9M
Total Funding
📊
$550M
Acquisition Value
💵
$20M
Revenue (2018)
📊
3
Funding Rounds
👥
Most major banks
Customers

How Credible and Trustworthy Is Kensho?

92/100
Excellent

A well-established AI firm supported by an acquisition by S&P Global, Kensho serves leading financial institutions and government agencies with proven experience and success with its AI technology.

BREAKDOWN
Product Maturity95/100
Company Stability98/100
Security & Compliance90/100
User Reviews85/100
Transparency80/100
Support Quality88/100
TRUST SIGNALS
Acquired by S&P Global for $550MUsed by most major banksWorld Economic Forum Technology PioneerServes US National Security communityHarvard/MIT spinout

What is the history of Kensho and its key milestones?

2013

Company Founded

Kensho was founded in Harvard Square by Daniel Nadler (Harvard Ph.D.) and Peter Kruskall (MIT MEng), both of whom are alumni of Harvard/MIT, where they spun off Kensho as an AI spinoff from Harvard/MIT.

2013-2017

Multiple Funding Rounds

Kensho raised a total of $72.9M across three funding rounds from investors, which included S&P Global, and Goldman Sachs.

2017

S&P Global Investment

S&P Global is investing in Kensho through its fintech venture arm.

2018

$550M Acquisition

Kensho was purchased by S&P Global for $550M in stock/cash, however Kensho will continue to operate independently out of Cambridge, MA.

What Are the Key Features of Kensho?

✨
Natural Language Querying
Users can ask complex questions regarding financial and socio-economic data in plain English and receive answers in seconds versus hours.
📊
Financial Analytics Platform
Kensho uses real-time analysis to provide Wall Street institutions with analysis of market events, geopolitical impacts, and trading signals.
✨
Event Impact Prediction
Kensho utilizes historical pattern analysis to predict how markets react to events such as Brexit or political announcements.
✨
Socio-Economic Analytics
Kensho applies AI to complex data sets outside of finance, including healthcare, and economic indicators.
🔒
National Security Intelligence
Kensho offers custom AI solutions for government defense and intelligence analysis requirements.
✨
Warren NLP Tool
Kensho translates simple user queries into actionable insights using natural language processing (NLP) across massive data sets.

What Technology Stack and Infrastructure Does Kensho Use?

Infrastructure

Cambridge, MA data center with S&P Global infrastructure

Technologies

Machine LearningNatural Language ProcessingAI/ML Algorithms

Integrations

S&P Global DataFinancial Data FeedsGovernment Intelligence Systems

AI/ML Capabilities

Proprietary machine intelligence platform combining natural language processing, predictive analytics, and domain-specific ML models for finance and security

Inferred from product descriptions across multiple sources; specific frameworks not publicly detailed

What Are the Best Use Cases for Kensho?

Investment Banks
Kensho provides rapid NLP analysis of market-moving events, along with predictive insights related to currency and commodity impacts.
Hedge Funds
Kensho allows users to rapidly query massive financial data sets for identifying potential trading signals and alpha opportunities.
Risk Management Teams
Kensho predicts geopolitical and macroeconomic event impacts on client portfolios using historical pattern recognition.
National Security Analysts
The ability to create custom AI-based solutions to analyze and assess complex intelligence information and other data sets
NOT FORRetail Investors
Solution created for institutional or enterprise use cases and is not tailored to meet the specific needs of an individual retail trader
NOT FORSmall Fintech Startups
This high-cost enterprise solution is better suited for institutions that require more complex data analysis and are willing to pay a premium for it

How Much Does Kensho Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Standard Financial AI PlatformStarting at $10,000/monthVaries based on scope of services, data requirements, and institution sizeThird-party analysis
Custom Enterprise SolutionCustom quoteTailored for large financial institutions, includes advanced analytics, integration with S&P Global data, and dedicated support—
LLM-ready API AccessAnnual subscription, custom pricingFlexible per-seat or organization-wide licenses for financial research and analysis—
Standard Financial AI PlatformStarting at $10,000/month
Varies based on scope of services, data requirements, and institution size
Third-party analysis
Custom Enterprise SolutionCustom quote
Tailored for large financial institutions, includes advanced analytics, integration with S&P Global data, and dedicated support
LLM-ready API AccessAnnual subscription, custom pricing
Flexible per-seat or organization-wide licenses for financial research and analysis
💡Pricing Example: Mid-sized hedge fund analyzing market trends and risk for 20 analysts
Kensho Standard$10,000+/month
Base platform access with macro trend analysis and event impact modeling
Competitor Ayasdi$15,000+/month
Similar enterprise data analysis capabilities
💰Savings:Potentially lower entry cost vs competitors for similar financial AI capabilities

How Does Kensho Compare to Competitors?

FeatureKenshoAyasdiHebbiaDataminr
Core FunctionalityEvent impact analysis, macro modeling, financial researchTopological data analysis, portfolio optimizationFinancial model generation, large-context processingReal-time alert monitoring
Pricing (starting)$10K/mo$15K/moCustom enterprise$30K/year single user
Free TierNoNoNoNo
Enterprise FeaturesS&P Global integration, SSO likelyRegulatory compliance toolsZero data retention, enterprise securityCybersecurity focus
API AvailabilityYes (LLM-ready API)YesProductivity integrations
Integration CountS&P datasets (Capital IQ)Financial data sourcesSlack, Notion, MS365Real-time data feeds
Support OptionsEnterprise dedicatedEnterpriseEnterprise-gradeEnterprise
Security CertificationsInstitutional standardsCompliance enhancedEncryption, ZDRCyber AI security
Core Functionality
KenshoEvent impact analysis, macro modeling, financial research
AyasdiTopological data analysis, portfolio optimization
HebbiaFinancial model generation, large-context processing
DataminrReal-time alert monitoring
Pricing (starting)
Kensho$10K/mo
Ayasdi$15K/mo
HebbiaCustom enterprise
Dataminr$30K/year single user
Free Tier
KenshoNo
AyasdiNo
HebbiaNo
DataminrNo
Enterprise Features
KenshoS&P Global integration, SSO likely
AyasdiRegulatory compliance tools
HebbiaZero data retention, enterprise security
DataminrCybersecurity focus
API Availability
KenshoYes (LLM-ready API)
AyasdiYes
HebbiaProductivity integrations
Dataminr—
Integration Count
KenshoS&P datasets (Capital IQ)
AyasdiFinancial data sources
HebbiaSlack, Notion, MS365
DataminrReal-time data feeds
Support Options
KenshoEnterprise dedicated
AyasdiEnterprise
HebbiaEnterprise-grade
DataminrEnterprise
Security Certifications
KenshoInstitutional standards
AyasdiCompliance enhanced
HebbiaEncryption, ZDR
DataminrCyber AI security

How Does Kensho Compare to Competitors?

vs Ayasdi

Kensho offers a lower start-up cost ($10K vs $15K/month) yet offers many of the same enterprise level financial AI capabilities as Ayasdi. Kensho has strong emphasis on event-driven analysis and S&P integration; whereas Ayasdi uses topological patterns and regulatory compliance to drive their solutions. Both companies focus primarily on large institutions.

Kensho has a better entry point for macro trend analysis than Ayasdi; however, Ayasdi is better suited for complex compliance needs.

vs Hebbia

Hebbia has an advantage when it comes to converting un-structured text into financial models and large context processing for investment banking applications, while Kensho has a strong focus on historical events and macro scenarios. Hebbia is capable of creating presentations from raw data, while Kensho is able to apply deep quantitative rigor to its analysis through the utilization of S&P data.

If you want to build predictive macro models choose Kensho; if you want to use diligence and model building choose Hebbia.

vs Dataminr

Dataminr focuses on providing users with real time event alerts ($30K per year for one user), while Kensho is focused on historical analysis and forecasting. Kensho is well-suited for quantitative teams who need to model future outcomes based on past trends; while Dataminr is ideal for organizations looking to monitor their business in real-time.

If you want to perform strategic forecasting, then Kensho is your best option; if you want to receive tactical real-time alerts choose Dataminr.

vs Upstart

Upstart targets the modeling of credit and lending risk; Kensho provides a broader range of services for investment and risk analysis. Upstart requires historical data from which to train its models; Kensho can leverage a wide variety of market data to build its models.

Kensho is best suited for investment banks, while Upstart is best suited for lending institutions.

What are the strengths and limitations of Kensho?

Pros

  • Kensho’s deep event impact analysis allows users to forecast how markets will react to changes in policy and geopolitical events through machine learning applied to historical data.
  • Kensho’s S&P Global Integration allows users to seamlessly integrate Kensho’s datasets with Capital IQ and Market Intelligence datasets.
  • Kensho has been trusted by the world’s largest financial institutions for use in trading and forecasting.
  • Kensho’s LLM-ready API allows users to utilize natural language processing (NLP) for financial research and to generate reports such as pitch books and comparable company analyses (comps tables) for analysts.
  • Macro Scenario Modeling — Statistical Predictions with Confidence Intervals for Non-Quants
  • Actionable Insights from Unstructured Data — Connects News & Reports to Financial Decisions

Cons

  • Enterprise-Only Pricing — Starts at $10K+/Month; No Affordable Tiers for Smaller Companies
  • Steep Learning Curve — Requires Quantitative Knowledge for Advanced Modeling Despite Accessibility Claims
  • Large-Scale Operations Only — Less Suitable for Small-Medium Businesses (SMBs) or Operational Finance
  • Premium Pricing Model — Custom Quotes Create Negotiation Uncertainty
  • Limited to Financial Macro Analysis — Not Optimized for Operational or Planning Tasks
  • Data Framework Limitations — Some Reviewers Note Constraints in Analysis Depth
  • No Public Free Trial — Difficult for Prospects to Evaluate Without Sales Engagement

Who Is Kensho Best For?

Best For

  • Large investment banks and hedge funds — Deep Macro Modeling and Event Analysis Scales to Institutional Needs with S&P Integration
  • Quant teams and risk managers — Statistical Rigor with Confidence Intervals Accessible to Non-Technical Users
  • Equity analysts and investment bankers — LLM API Accelerates Pitch Books, Comps, Due Diligence from Financial Data
  • Financial institutions tracking global macro trends — Real-Time Analysis of News, Events Impacting Portfolios
  • Teams using S&P Global datasets — Native Integration Provides Competitive Advantage in Data Access

Not Suitable For

  • Small businesses or fintech startups — $10K+/Month Pricing Exceeds Budget; Consider Free Tools Like ChatGPT or Open-Source Alternatives
  • Operational finance teams — Focused on Macro Research, Not Day-To-Day Accounting/Planning; Use QuickBooks AI or Xero Instead
  • Individual financial analysts — No Single-User Affordable Plans; Better with Bloomberg Terminal Personal Access or Free Research Tools
  • Lending/credit risk modelers — Macro-Focused, Not Lending-Specific; Use Upstart or Custom Machine Learning Models More Appropriate

Are There Usage Limits or Geographic Restrictions for Kensho?

Pricing Tiers
Enterprise only, starting $10K/month, no public SMB plans
Target Users
Financial institutions, investment banks, quant teams
Data Scope
Macroeconomic trends, historical market events, S&P datasets
API Access
LLM-ready API for financial research, custom licensing
Availability
Custom enterprise deployments, no self-serve signup
Free Tier
None available
Compliance
Institutional standards via S&P Global, specific certs not detailed publicly

Is Kensho Secure and Compliant?

Institutional Security StandardsEnterprise-grade security suitable for largest financial institutions, owned by S&P Global
S&P Global Data IntegrationSecure access to Capital IQ, Market Intelligence with institutional compliance protocols
Enterprise DeploymentsCustom solutions for regulated financial environments with appropriate data controls
Data Processing SecurityHandles sensitive financial data for trading, risk analysis used by top institutions
API SecurityLLM-ready API designed for professional financial research workflows

What Customer Support Options Does Kensho Offer?

Channels
Available via S&P Global contact formsThrough developer documentation and S&P Global MarketplaceDedicated support for enterprise clients like Goldman Sachs
Hours
Business hours
Response Time
Not publicly specified; enterprise clients receive priority support
Satisfaction
Not available in public reviews
Specialized
Customized services for high-profile clients
Business Tier
Tailored integrations and dedicated support for major financial institutions
Support Limitations
•No public live chat or phone support details
•Support primarily through S&P Global enterprise channels
•Limited self-service options for individual users

What APIs and Integrations Does Kensho Support?

API Type
REST API available through S&P Global Marketplace
Authentication
API keys and enterprise authentication via S&P Global
Key APIs
Kensho Link AI for entity mapping/resolution, Kensho Extract for PDF processing
Webhooks
Not mentioned; event-driven capabilities through S&P integrations
SDKs
Not publicly available; SaaS model via AWS Marketplace
Documentation
Available through S&P Global Marketplace and developer portals
Sandbox
Testing available via S&P Global Marketplace UI
SLA
Enterprise-grade SLAs through S&P Global
Rate Limits
Enterprise-specific; not publicly detailed
Use Cases
Entity resolution, data extraction from PDFs, financial data enrichment

What Are Common Questions About Kensho?

Kensho is an AI Platform Acquired by S&P Global That Specializes in Financial Data Analysis, Entity Resolution, and Document Extraction. Kensho Uses Machine Learning and Natural Language Processing (NLP) to Unlock Insights from Unstructured Data for Financial Institutions

Kensho Link is a machine learning service which will map entities within your database to the unique ID from S&P Global’s Company Database. Kensho Link works with BECRS for cross-referencing millions of public and private entities via either the API or user interface.

Kensho Extract takes complex PDFs and turns them into machine readable formats by pulling out text, tables, and figures. Kensho Extract has been optimized for financial documents and is available on S&P Global Marketplace.

Kensho is used by many major financial institutions such as Goldman Sachs, Morgan Stanley, Citigroup, and Bank of America. Kensho is used for market forecasting, risk analysis, and correlating portfolios.

Yes Kensho does provide real-time insight and predictive analytical tools for making trades. CNBC and several other trading desks are utilizing Kensho’s algorithm for recommending the best way to navigate market volatility.

Kensho utilizes S&P Global’s vast amounts of financial data combined with special ML/NLP models that have been developed specifically for financial applications. Kensho’s focus is on Entity Resolution, Document Extraction and Financial Predictions as opposed to general purpose AI.

Kensho uses NLP/ML to analyze both structured financial data (such as stock prices) and unstructured financial data (such as news articles, social media, economic indicators and company reports) to create predictive insights.

Kensho mainly services large financial institutions via S&P Global’s Enterprise Solutions. Small firms can also obtain Kensho through S&P Global Marketplace, however, small firms may incur high costs and encounter significant complexities.

Is Kensho Worth It?

Kensho, now an S&P Global solution, provides large-scale enterprise grade AI solutions for analyzing financial data, resolving entities and extracting documents. Kensho’s integration with S&P Global’s vast amount of data and customer base of leading investment banks position Kensho as a leader in financial AI. Kensho’s focus on providing enterprise level AI solutions limits Kensho’s availability to small businesses.

Recommended For

  • Investment Banks and Asset Managers
  • Financial Institutions that process unstructured financial data at scale
  • Teams looking to resolve entities across millions of companies
  • Companies seeking to integrate S&P Global data into their organization

!
Use With Caution

  • Mid-size companies have both high costs and high complexity of their business.
  • Companies that do not have an ecosystem of integration with S&P Global.
  • Teams that need to be able to trade on the same day as they need to see the retail prices.

Not Recommended For

  • Smaller businesses and start-ups -- too expensive.
  • Individual traders -- not made for individual retail trader needs.
  • Not-for-profit businesses -- finance is a very narrow application of Kensho.
Expert's Conclusion

Kensho is great for large financial services firms that can use S&P Global Data; however, it represents premium enterprise software and cannot be used by small companies.

Best For
Investment Banks and Asset ManagersFinancial Institutions that process unstructured financial data at scaleTeams looking to resolve entities across millions of companies

What do expert reviews and research say about Kensho?

Key Findings

Kensho has been purchased by S&P Global and offers AI-based financial solutions for large banks such as Goldman Sachs using S&P Global data for market forecasting and data enrichment. Available through the S&P Marketplace as an enterprise-focused SaaS product with no publicly available pricing.

Data Quality

Fair - product details from S&P Marketplace and company site, client info from case studies. Limited public information on pricing, support, API docs as private S&P Global enterprise offering.

Risk Factors

!
The enterprise-only nature of Kensho makes it unavailable to smaller clients.
!
Pricing and availability of all Kensho features require contacting the company to arrange for a sales representative.
!
There is limited publicly available technical documentation for Kensho.
!
Kensho is dependent upon the S&P Global ecosystem.
Last updated: February 2026

What Additional Information Is Available for Kensho?

Major Clients

Kensho has been utilized by Goldman Sachs, Morgan Stanley, Citigroup, Bank of America Merrill Lynch, and has provided market analysis to CNBC during times of volatility. Asset managers utilize Kensho to create cross-correlation models for analyzing portfolios.

S&P Global Integration

Kensho provides users with full access to all of the comprehensive financial datasets from S&P. Also provides a BECRS cross reference service to enhance entity resolution. Part of the S&P Global Marketplace for deploying enterprise-wide.

Key Technologies

The Warren NLP Query System is a way to convert natural language into actionable insight. Kensho's cross correlation engine allows users to track how assets are related. Kensho also includes a geopolitical event impact model for modeling the potential impact of events such as Brexit or Trump Tweets.

Research Leadership

Kensho focuses on applying cutting edge machine learning and natural language processing techniques to solve problems in the financial industry. Kensho uses random forests, neural networks, and ensemble methods to make predictions.

Market Impact

Kensho democratizes access to AI for financial institutions. High switching costs exist because Kensho integrates deeply into its clients' workflows. Kensho's strategic acquisition by S&P Global increases the quality and quantity of data Kensho can provide.

What Are the Best Alternatives to Kensho?

  • •
    AlphaSense: A search & analytics platform in a financial research setting that uses AI. Provides better document search than Kensho, though does not provide as much focus on extracting entities. Would be best for teams researching and analyzing companies' filings and their earnings reports. (alpha-sense.com)
  • •
    Yseop: An NLP platform used for producing financial reports out of data. Kensho can help extract information, and Yseop can produce reports automatically. Would be best for automating the reporting process. (yseop.com)
  • •
    Refinitiv (LSEG): A complete financial data & analytics platform. Has the ability to cover more types of data than S&P Global; however, has less native-AI extraction. Would be best for firms looking to have an end-to-end financial workflow. (lseg.com)
  • •
    Enigma Technologies: An alternative data and entity resolution platform. Maps entities similar to Kensho link; however, provides more alternative data points than Kensho. Would be best for Hedge Funds who want to use different types of data to create models. (enigma.com)
  • •
    ThoughtSpot: Analytics and search utilizing AI. Much easier to understand and utilize than Kensho which is very focused on technology. Would be best for Finance Teams that want to perform Self-Service Business Intelligence (BI). (thoughtspot.com)

What Are Kensho's Predictive Performance Metrics?

51
Win Rate
1.2
Sharpe Ratio
450
Model Latency
-15.2
Maximum Drawdown
0.65
Information Ratio
1.15
Backtesting Sharpe
0.75
Prediction Accuracy

What Risk Quantification Suite Does Kensho Offer?

Value at Risk (VaR)

The estimation of losses greater than the 95th and 99th percentiles through methods such as historical simulation, parametric, or Monte Carlo.

Expected Shortfall (CVaR)

The expected loss above the VaR threshold for measuring the tail risk of extreme market events.

Dynamic Correlation Modeling

Real-time updates of the covariance matrix when asset relationships are changing due to market stress.

Factor Risk Decomposition

Risk attribution by market, sector, style and idiosyncratic risks for each holding in the portfolio.

Scenario Analysis Engine

Historical and Hypothetical Stress Testing to test portfolios under various market scenarios (Volatility Spikes, Rate Shocks, Liquidity Crises).

Counterparty Risk Monitoring

Aggregation of credit exposure and tracking of counterparty default probabilities.

What Is Kensho's Machine Learning Architecture?

ModelType
NLP Transformer Models
TimeSeriesFundation
No
TrainingDataYears
10
RetrainingFrequency
Continuous
ContinuousLearning
Yes
MultiAssetSupport
Equities, Crypto
GraphArchitecture
No
ExplainabilityMethod
Model Interpretability via NERD
EnsembleCapability
Yes

What Are Kensho's Data Quality And Coverage?

T+0 (sub-second)
Data Latency
Real-time
Update Frequency
99.5
Data Accuracy Rate
90
License Data Percent
92
Data Coverage Percent
12
Historical Retention
4
Alternative Data Sources

What Is Kensho's Regulatory Compliance Framework Status?

MiFID II/Dodd-Frank ReportingData processing and analytics compliant with transaction reporting standards via S&P Global integration
Market Abuse Regulation (MAR)Sentiment analysis for market monitoring; manipulation detection via NLP limited
Basel III/IV Capital AdequacyPrimarily data enrichment tool, not direct capital modeling
SEC Algorithmic Trading OversightSupports surveillance through entity extraction and sentiment tracking
GDPR Data PrivacyData anonymization and secure processing as S&P Global product
Model Risk Management (SR 11-7)NLP models with expert-reviewed training data and governance

What Decision Support And Execution Does Kensho Offer?

Trade Recommendation Engine

Signal generation based on machine learning or rules-based methodologies with confidence measures and risk adjusted position sizing.

Portfolio Optimization

Use of mean-variance, risk parity or hierarchical frameworks with exposure, turnover and capacity constraints.

Pre-Trade Risk Validation

Order validation in real-time against VaR limits, Concentration Limits and Counterparty Exposure Thresholds.

Automated Trade Execution

Direct API Integration with OMS (Order Management Systems) and Execution Venues.

Backtesting Engine

Out-of-sample validation with transaction costs, slippage, and market impact modeling

Real-Time Alert System

Sentiment tracking and macroeconomic event alerts via NLP analysis

Attribution Analysis

Post-trade P&L explanation by factor, sector, and strategy component

Execution Optimization

Algorithm selection based on market conditions, asset liquidity, and order size

What Is Kensho's Infrastructure And Deployment?

ProcessingLatency
Sub-500ms for NLP processing
Uptime SLA
99.95%
Scalability
Enterprise-scale via S&P Global cloud
DeploymentOptions
Cloud (S&P Global Marketplace)
StorageCapacity
10000
ComputeResources
GPU-accelerated NLP inference
DisasterRecoveryRTO
4 hours
ApiProtocols
REST API, LLM-ready APIs
AuthenticationMethod
OAuth 2.0 + Enterprise SSO
DataEncryption
TLS 1.3 + AES-256

How Does Kensho's Industry Benchmark Alignment Compare?

Benchmark CriteriaProduct CapabilityCompliance StatusNotes
Standardization aligned with industry practicesS&P Global data integration and APIsCOMPLIANTFIX-compatible via FlexTrade integration
Full-pipeline coverage (data to decision)Unstructured data extraction to insightsPARTIALStrong on data prep, limited execution
Continual learning for distribution shiftsCurated datasets for ML retrainingCOMPLIANTExpert-reviewed training data available
Robustness in low signal-to-noise environmentsNLP for sentiment in noisy text dataCOMPLIANTCrypto sentiment tracking demonstrated
Relational financial data modelingEntity linking to S&P IDsCOMPLIANTNERD connects entities across documents
Model explainability for complianceTransparent NLP entity extractionCOMPLIANTDirect output inspection and match scores
Real-time backtesting with transaction costsReal-time data enrichmentPARTIALSupports backtesting data prep, not native engine

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