Research-grade engineering for federal data and AI.
Complexity Labs, Inc. is a New York based technology small business: a Delaware corporation incorporated in 2025, SBA self-certified, active in SAM.gov. We bring data scattered across decades of systems into one trustworthy place, then put machine learning and accountable AI to work on it. Everything we build is deployed inside your own cloud tenant, integrated through APIs so your source systems stay unmodified, and handed back on open interfaces. A person approves every consequential step, and every automated decision is logged and traceable.
Core competencies
Data modernization
Move data off aging systems into the cloud, every record verified, none lost, and federal retention rules preserved.
Legacy System MigrationCloud Migration (AWS, Azure, Microsoft Fabric)Records Migration off On-Premise StorageVerified Record-by-Record TransferFederal Retention Rules (SEC Rule 17a-4, FINRA)Rebuilds That Keep Serving TrafficExtend Rather Than ReplaceSource Systems Left UnmodifiedAPI-Based IntegrationPost-Quantum Migration (ML-KEM / FIPS 203, ML-DSA / FIPS 204)Crypto-Agility and Algorithm-Agnostic LibrariesHarvest-Now-Decrypt-Later Exposure AuditsInfrastructure That Clears Security Review
Data platforms
One trusted home for data held in many systems, fed live rather than by overnight batch, with access controls and a full audit trail.
AI-Ready Data FabricIngestion from Files, Object Stores, Databases, Warehouses, Streams and REST APIsBatch and Streaming as One ProgramEvent-Propagation PipelinesMedallion Architectures (Bronze, Silver, Gold)Incremental Deltas and Full RecomputeRestart RecoveryDeterministic SQL Graphs, Reproducible Run to RunSemantic Catalog, Concept Matching, Schema-Drift MonitoringData Lineage and Quality ScoringAccess Controls and a Full Audit TrailGoverned SELECT-Only Query ServiceLive Feeds Instead of Overnight ReportsPipelines That Survive an Audit
Machine learning
From raw data to models running in production, watched for drift, with data-quality checks built into the pipeline.
Raw Data to Production ModelsStatistical Learning Theory and PAC LearningModel VerificationBias Testing Under the NIST AI Risk Management FrameworkDrift and Anomaly Detection in ProductionEarly Warning When Accuracy SlipsData-Quality Checks Inside the PipelineRetrieval-Grounded Systems That Cite Their SourcesAdversarial ML and Media AuthenticationTraffic Video Analytics (IEEE-published)Streaming and Sketching: Morris Counters, Count-Min Sketches, Locality-Sensitive HashingRandomized Approximation With Tunable Accuracy and ConfidenceProfiling Estates Too Large to ScanPyTorch, scikit-learn
Auditable AI
Assistants and agents grounded in your own data, with a person approving every consequential step and every action logged.
Document-Processing AgentsDraft-and-Approve: A Human Checkpoint on Every Consequential StepExtraction from PDFs, Scans and CAD ExportsIndexing and Rule-Checking Against Configurable RulesetsGaps and Conflicts Flagged With Citations to Document and RuleAnswers Grounded Only in Your Document StoreCitations on Every AnswerPII Detection and RedactionAction Log: Every Tool Call, Document and DecisionPlain English Questions Turned Into SQL a Person Reads FirstNo Language Model in the Execution PathModel Output Treated as UntrustedRecords Requests Answered by Lookup, Not Investigation
Differentiators
- We extend, we do not replace. The systems you run today keep serving traffic while we build alongside them. No rip-and-replace program, no downtime window to negotiate.
- Deployment inside your own tenant. The platform runs in your cloud account, on your storage, under your identity provider. Your data does not leave it.
- Integration through APIs. We connect to source systems through their published interfaces and leave those systems unmodified, so nothing we do adds to the code your team already maintains.
- No lock-in. Open interfaces throughout. You can take the platform over in-house, or take it elsewhere. If we do our job, you could leave.
- A person approves every consequential step. Any step that creates, modifies or deletes waits for a human checkpoint. Proposed SQL is read by a person before it runs, and no language model sits in the execution path.
- Every automated decision is logged and traceable. The action log records each tool call, retrieved document and decision, so “why did the system do that?” is a lookup rather than an investigation.
- Inference stays on U.S. soil, and your data is never used to train anyone else’s models.
- Aligned to NIST. The Cybersecurity Framework, Special Publication 800-53 controls, and the AI Risk Management Framework, treated as design inputs rather than a compliance pass at the end. Records requests and oversight are designed for, not retrofitted.
- A research-grade team. Doctoral research in algorithms and complexity, Ivy League graduate training in computer science, peer-reviewed publication with the Institute of Electrical and Electronics Engineers, AWS certified, U.S. citizens and clearance eligible.
- Working software, not slideware. We arrive with NRV and Machina already built, so an engagement starts from a running platform instead of a discovery phase.
The tools we bring
NRV, our data fabric
- Turns files, databases, warehouses, live streams and web services into one estate you can query, without replacing what you run today
- Batch and live data in one pipeline, so a change at the source reaches the report on its own
- Plain English questions become database queries a person reads and approves before anything runs
- Full lineage, a governed read-only query service, and a warning when a source system quietly changes shape
Working software: 121 automated tests, plus trials against real databases, object storage and streaming brokers. Demonstrated on federal transportation data.
Machina, our document agents
- Sends the document backlog through agents that extract, index, check against your rulebook, and draft the next action with citations
- Gaps and conflicts are flagged with a citation to both the document and the rule
- A person reviews and approves before anything is final, and PII is detected and redacted before anything leaves the building
- Runs in your tenant alongside NRV
Delivery record
Delivered by our engineering leadership on regulated financial platforms at prior employers, at institutional scale. Stated qualitatively: these were their engagements, not Complexity Labs contracts.
- Daily investment accounting: built and ran the cloud data pipeline behind daily investment accounting at a global asset manager, feeding valuation checks, settlement reconciliation and daily profit and loss.
- Records migration: moved decades of records off aging on-premise storage into the Microsoft and Amazon clouds, every file verified and federal retention rules (Securities and Exchange Commission Rule 17a-4, FINRA) preserved.
- Regulatory reporting: built the engine that slices portfolios for capital and solvency reporting, reconciling several independent ratings and classification systems into one view.
Who you work with
- Research grade rigor: graduate training in computer science at an Ivy League university, doctoral research in algorithms and complexity underway at the University of Cambridge, and peer-reviewed work published by the Institute of Electrical and Electronics Engineers on traffic intersection video analytics.
- Certified and cleared: AWS Certified Data Engineer and Cloud Practitioner. United States citizens, clearance eligible. Security aligned to National Institute of Standards and Technology guidance: the Cybersecurity Framework, Special Publication 800-53, and the AI Risk Management Framework.
How we deliver
We consult with products in hand. Engagements move faster when the platform work is already done, so we start from NRV and Machina rather than from a blank repository, and we spend the engagement on your data and your rules instead of on plumbing. Work lands in your environment continuously, in small reviewable pieces, against your security review rather than around it. What we hand over is running software, its lineage, its tests and its documentation, on interfaces your own engineers can pick up.
NAICS codes
- 541511 Custom Computer Programming Services (primary)
- 541512 Computer Systems Design Services
- 541519 Other Computer Related Services
Registration and contact
- UEI
- SACZBXUXLAL5
- CAGE
- 16YX0
- NAICS
- 541511 (primary) · 541512 · 541519
- Entity
- Delaware corporation, incorporated 2025
- Location
- New York
- Status
- SBA self-certified small business · SAM.gov active
- Contact
- Ashvin Jagadeesan, President
- ashvin@complexitylabs.co
- Web
- complexitylabs.co
Technology
Python · SQL · PySpark · Delta Lake · Parquet · Apache Kafka · PostgreSQL · Snowflake · Amazon Web Services · Microsoft Azure · Microsoft Fabric · PyTorch · scikit-learn · Docker
Schedule a capabilities briefing. Ashvin Jagadeesan, President · ashvin@complexitylabs.co · complexitylabs.co · UEI SACZBXUXLAL5 · CAGE 16YX0 · SBA self-certified small business