Data Customization & Pipeline
The infrastructure behind the dataset you can’t buy off the shelf
Most custom-build firms are selling engineering hours. algoseek has the software, hardware, and compute grid to build custom datasets, analytics, and pipelines to petabyte scale.
What We Build
Any field. Any aggregation. Any format. Any size.
If it existed as a standard product, you’d have bought it already. algoseek builds the specific thing: petabyte archives, order book products, custom indexes, client signals merged into production bars.
timestamp
2024-03-15 09:30:00
open
175.23
high
175.89
low
175.01
close
175.67
volume
1,284,500
vwap
175.44
buy_volume
742,100
sell_volume
542,400
nbbo_spread_avg
0.012
trade_count
3,847
client_signal_1
0.873
Pipeline Architecture
The pipeline you’d have to build yourself. Already running.
>algoseek builds and maintains every stage, source connectors through delivery, running in AWS or Equinix and delivering to the infrastructure you already use. Your operations team doesn’t inherit a system to babysit.
Sources
Exchange Feeds
Third-Party APIs
Client Data
Cloud Storage
Ingest
Connectors
Schema Detection
Format Parsing
Transform
Normalization
Cross-Reference
ASID / FIGI Mapping
AI/ML Matching
Quality
Schema Validation
Drift Detection
Completeness Check
Benchmark Compare
Deliver
S3 / Azure / GCS
Database
API / Kafka
SFTP / File Drop
Orchestration & monitoring across all stages · Alerts on drift, schema breaks, and delivery failures
Data governance and compliance at every stage
Cross-referencing via ASID, FIGI, and ISIN
algoseek handles upgrades and exchange spec changes
Ticker Plant as a Service
Use our ticker plant instead of building your own
Building a ticker plant and keeping it current with every exchange spec change is expensive and exhausting. Mercury, written in C++ and Assembly with zero external dependencies, does it as a managed service.
Processes raw PCAPs from all major exchanges
Normalizes raw binary data into standard or custom formats
Multicast, TCP socket, WebSocket, REST API, and Kafka output
Time-machine feed replay for backtesting and simulation
Cloud-based and data center deployment
Zero downtime through multiple volume explosions since inception
How It Works
From specification to production
Specify
The most expensive mistake in a custom build is a vague brief. algoseek writes a formal specification and sample data; nothing moves until you sign off on both.
Build
Fixed cost once the specification is complete. Engineering builds against the approved spec, so scope and cost stay where you agreed.
Validate
Bad data that passes QA quietly is worse than no data. Output is tested against your criteria: schema, completeness, benchmark comparison against known-good sources.
Deliver
Historical backfill and daily production updates land in your infrastructure, in the format your systems already consume.
Monitor
Exchange specs change and feeds break at inconvenient times; algoseek handles monitoring, alerting, maintenance, and every upgrade, so none of it falls to your team.
Use Cases
Two builds. Two different problems. Same infrastructure.
Custom OPRA NBBOUS Regulator
A US regulator required a custom OPRA NBBO from the full feed, delivered to the cloud at low latency. algoseek combined Mercury and its compute grid into regionally redundant infrastructure with 4-way arbitration for lossless capture under load. The result is a critical component of US regulatory infrastructure.
Custom TWAP BarsBulge Bracket Bank
A bulge bracket bank’s index structuring team needed historical and real-time custom one-minute TWAP bars for US equities, used daily to price some of the most important US indexes. algoseek built the feed handler, computed the full history, and delivers at scale to the bank and its third-party Calculation Agents concurrently.
Common questions
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How long does a custom data build take?
It depends on the complexity and the work required. The most important phase is the specification: capturing your requirements, writing a detailed spec, and creating sample data for your sign-off. algoseek provides a fixed cost for projects once the specification is complete. We focus on getting the spec right because that is what determines whether the output is right.
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Can you work with third-party data we don’t own?
Yes. algoseek can access third-party data on your behalf, acting as your service provider. We handle the vendor relationship, data ingestion, normalization, and quality assurance. You receive the ready-to-use output.
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What formats and delivery methods are supported?
CSV, Parquet, JSON, and custom delimited formats. Delivery to S3, Azure Blob, GCS, databases, SFTP, API endpoints, and Kafka streams. We adapt to your existing workflow.
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Is historical backfill available?
Yes. algoseek’s archive covers US equities back to 2007, options and futures back to 2014. Custom datasets can be backfilled over the full history and then kept current with daily production updates.
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Can I combine algoseek data with my own proprietary data?
Yes. Custom datasets can include fields calculated from algoseek data, your proprietary data, or both. We can ingest your data into the pipeline and merge it with algoseek fields during processing.
Other Services
Cloud Infrastructure
Colocation, managed hosting, and low-latency market data feeds in one facility.
Data Supplier Solutions
Tools and managed services for data vendors to build, sell, and deliver data products.
ArdaDB
Subsecond SQL queries on the full algoseek historical archive. Available for every data package.
Talk to Us
Describe the data you need
Specification, sample data, and a fixed cost, all before any work begins.