SAM.gov activeEnterprise & government softwareWashington D.C. · Maryland · VirginiaSBA small business
Capabilities
Every capability, with its deliverable and its evidence.
Eight areas of AI, data, cloud and compliance engineering for federal and enterprise programs — each with what you get, what the artifact looks like, and the experience behind it.
Core capability — delivered work behind itGrowing capability — engineering depth, building the record
01
GenAI Delivery & Enablement
Core capability
Production generative AI workflows and services, built in your environment and handed to your team. Evidence: founder-built GenAI foundational-layer infrastructure at a large regulated financial institution — founder-level experience, not Fairs Place contract history.
What you get
A working agent or workflow deployed in your environment
An evaluation harness with a baseline and a pass/fail gate
Prompt and context artifacts versioned in your source control
A runbook and a live handover session with your engineers
Sample artifact — evaluation report240 cases
Exact match base 0.780.81
Citation validity base 0.960.97
p95 latency limit 3.0s1.9s
Cost / 1k calls limit $6.00$4.10
No regression vs. baselinerelease permitted
02
MLOps & GenAIOps
Core capability
Ten years of feature-store and ML-pipeline discipline, applied to generative AI. Founder-level experience at a regulated financial institution and a federal AI/ML systems integrator supporting DoD programs.
What you get
Versioned context and prompt artifacts, not tribal knowledge in a chat window
A reproducible evaluation pipeline on every model or prompt change
Drift and regression monitoring for LLM outputs in production
Canary and rollback procedures, tested rather than documented
citation validity −0.06, auto-rollback in 4 minutes
ctx-v1.2superseded
retained for reproducibility
03
Context & Feature Store Engineering
Core capability
Feature stores gave ML consistent, low-latency data at inference time. Context stores do the same for GenAI. We have built both.
What you get
A context schema: what is stored, for how long, and who may read it
Retrieval and ranking tuned for relevance, with the measurement to prove it
A per-decision retrieval trace an auditor can actually read
A freshness and eviction policy, so stale context stops poisoning answers
Retrieval tracequery 8f31c
SOP-427 §3.2 4d0.91 used
Memo-118 11d0.84 used
SOP-402 §1 612d0.77 stale
Draft-09 unapproved0.74 dropped
Answer cites 2 of 2 sources usedtraceable
04
Cloud Platform & Site Reliability
Core capability
Production cloud infrastructure and SRE-grade operations, including runtime systems that served millions of users daily.
What you get
Infrastructure as code, reviewed and versioned like application code
Defined SLOs with alerting bound to them, not to CPU graphs
An on-call runbook your team can execute without us
Incident practice and written post-incident reports
Sample artifact — service SLO sheet
99.95%
Availability
400ms
p95 latency cap
50%
Error budget freeze
Restore-from-backup drill — quarterlyPaging owner — named engineer
05
Health IT Modernization & Compliance
Core capability
Eight months (May–December 2022) as lead engineer at a HIPAA-regulated digital pathology company: HL7 integrations connecting pathology systems to clinical and laboratory systems, under an active compliance program. Founder-level experience, not Fairs Place contract history.
What you get
HL7 interface build with segment-level mapping documentation
Conformance and negative-path test suites against sample messages
A PHI data-flow diagram, minimum-necessary review and audit logging
A cutover plan with a rehearsed rollback
HL7 interface mapORU^R01
MSHrouting key
PIDPHI, masked in logs
OBRaccession key
OBXcoded result
ACKretry 3×, dead-letter
Conformance suite64 of 64 passing
06
Security & Compliance Engineering
Core capability
Compliance-driven engineering against named frameworks — NIST AI RMF, NIST SP 800-171 and HIPAA — so the control evidence is produced with the software, not reconstructed afterwards.
What you get
A control-to-implementation mapping with evidence named per row
CUI and PHI handling procedures written to be audited
An AI risk review per agent workflow, mapped to NIST AI RMF functions
A tool and data-boundary register, approved in writing
Control mapping extract
Control
Implementation
Evidence
3.1.1
Least-privilege repository and cloud roles
role matrix
3.3.1
Audit logging on PHI and CUI paths
log sample
3.4.3
Change control via reviewed pull requests
PR history
3.13.11
Encryption at rest and in transit
config export
AI RMF
Per-workflow risk review, MAP and MEASURE
review memo
07
Application Development & Delivery
Growing capability
Web and browser-based applications end to end: architecture, build, test, review, release. Shipped and store-reviewed products, not prototypes.
What you get
A specification and test suite that exist before the implementation
CI with test, lint and build gates from the first commit
A release checklist, versioned deployments and a rollback path
Architecture documentation for the team that inherits it
Release checklist
Specification accepted by client lead
Tests green, coverage gate met
Dependency and secret scan clean
Agent-authored diffs human-reviewed
Rollback rehearsed in staging
Documentation and runbook updated
08
Mission Automation & Workflow Engineering
Growing capability
Five years of ML, data-processing and automation solutions at a federal AI/ML systems integrator supporting DoD programs — mission workflows automated in code, with the time saved measured.
What you get
A mapped current-state workflow with the manual steps timed
Automated pipelines with retries, alerting and a dead-letter path
Data-quality checks at every boundary, failing loudly
Before/after time-on-task measurement, so the saving is a number
Pipeline run
Ingest
1,284
Validate
1,271
Transform
1,271
Deliver
1,271
13 records quarantined with reasons queued.
Runtime vs. a 3.5h manual process6m 12s
Where we are headed next
The next capability areas we are investing in. Tell us if one of them is on your program — that is usually how they become the work.
Investing
Data governance & catalog
Cataloging, metadata management and lineage, alongside the pipelines we already build.
Investing
IAM & zero trust
Identity and access engineering, extending our SP 800-171 control work.
Investing
Accessibility & HCD
Section 508 conformance and user research on the applications we deliver.
Investing
Further accelerators
The Context Engine is the first of a planned set of reusable components.