Service Knowledge Systems

Put your institutional knowledge to work.

Your company already knows the answer. It's just buried in a wiki page from 2022, a closed support ticket, a contract PDF, or the head of someone who hasn't looked at it in months. I build RAG systems over that knowledge — documents, wikis, tickets, contracts — and turn it into a queryable, source-cited system your team can actually trust. Without leaking it to people who shouldn't see it.

8 wks Corpus to production
100% Answers source-cited
1 KPI Attached before we build

Most companies I meet don't have a shortage of knowledge — they have a shortage of access to it. The answer to a customer's question sits in a ticket from eighteen months ago. The right contract clause is buried in a PDF nobody indexed. The process someone figured out the hard way lives in their head, not in a doc. That's not a knowledge problem, it's a retrieval problem.

I build systems that fix the retrieval problem: document intelligence that actually understands your files, hybrid search that finds the right passage instead of the closest keyword, and answers that come back with the source attached. If an answer can't point to the document it came from, it doesn't ship.

What a knowledge system actually needs

Three things separate a system people trust from one they quietly stop using after the second wrong answer.

  • Document intelligence — parsing, chunking, and structure-aware ingestion across PDFs, wikis, tickets, contracts, and spreadsheets, so the tables and hierarchy your data depends on survive the process instead of getting flattened into noise.
  • Permissioned access — retrieval that respects the access controls you already have, so a system built to save time doesn't become the fastest way to leak something it shouldn't.
  • Freshness and source citations — every answer traces back to the exact document and section it came from, and the index stays in sync as source material changes, so stale answers get flagged instead of served with confidence.

Where this earns its keep

The clearest wins are places where people currently ask a colleague instead of searching: support teams answering the same question a hundred different ways, new hires re-learning what the last person already figured out, compliance teams hunting through contracts for a clause. I look for the process where faster, cited answers move a real number — time-to-answer, ticket deflection, onboarding time — and I start there.

The knowledge is already inside your company. Most of it just isn't findable. That's the gap I close.

The four pillars of a knowledge system.

Built in from the first sprint — not bolted on after the index ships.
01 / Ingestion
Document intelligence
Parsing, chunking, and structure-aware handling across PDFs, wikis, tickets, and contracts — tables and hierarchy preserved, not flattened into plain text.
02 / Memory
Institutional memory
Captures what's normally lost when someone leaves or a thread goes stale — decisions, past resolutions, tribal knowledge — as a living, queryable index.
03 / Access
Permissioned access
Retrieval respects your existing permission model. No answer surfaces a document the person asking isn't cleared to see.
04 / Trust
Source citations
Every answer traces to the exact document and section it came from, with freshness tracked so outdated answers get flagged, not served.
Document intelligencePermissionsCitationsFreshnessHybrid retrievalOn-prem option

Eight weeks, corpus to live.

Fixed scope, fixed price, weekly demos during the build.
01Audit

Map where the knowledge actually lives

We inventory the docs, wikis, tickets, and contracts scattered across your systems, and agree on the KPI — time-to-answer, ticket deflection, onboarding time — before a line of code is written.

02Architect

Design ingestion, permissions, and retrieval

Chunking strategy, permission mapping, and hybrid retrieval are designed together — fixed scope and price so there are no surprises mid-build.

03Build

Ingest, index, and ship into production

We build in sprints with weekly demos, index the real corpus, and deploy into your environment — not a sandbox with a handful of sample documents.

04Measure

Prove it against the KPI

We track the system against the number we set, tune retrieval quality and citation accuracy, and keep tuning until the value clears the cost.

Related work.

Knowledge systems rarely ship alone. These usually come with them.
Service / 02
RAG systems
Retrieval pipelines that put your institutional knowledge to work. Grounded, source-cited answers on your own data — without leaking it.
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Service / 01
Enterprise AI agents
Agentic workflows designed around your actual processes, not a demo — built, deployed, and tuned until they hold up in production.
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Service / 06
Decision intelligence
Analytics, dashboards, and predictive models that drive real decisions — built by someone who spent 15 years attaching dollars to outcomes.
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Service / 04
Compliance & governance
SOC 2 controls, HIPAA compliance, and deployments built for regulated industries — from day one, not bolted on later.
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Service / 07
Enterprise workflows
Multi-system orchestration across Salesforce, ServiceNow, SAP, and your custom APIs — finally talking, with an audit trail.
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Service / 03
AI infrastructure
Local model deployment and hardware builds for organizations that need their data to stay inside their walls. Nothing leaves the perimeter.
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Let's make your knowledge findable.

If your team burns hours hunting for answers that already exist somewhere in your docs, that's where we start. I'll tell you what it's worth before we build it.

Let's talk

Markets served.

Remote-first across the United States and internationally — including these markets.

New York City, New York (NY)

Los Angeles, California (CA)

Chicago, Illinois (IL)

Houston, Texas (TX)

Phoenix, Arizona (AZ)

Philadelphia, Pennsylvania (PA)

San Antonio, Texas (TX)

San Diego, California (CA)

Dallas, Texas (TX)

San Jose, California (CA)

Austin, Texas (TX)

Jacksonville, Florida (FL)

Fort Worth, Texas (TX)

Columbus, Ohio (OH)

Charlotte, North Carolina (NC)

Indianapolis, Indiana (IN)

San Francisco, California (CA)

Seattle, Washington (WA)

Denver, Colorado (CO)

Washington, District of Columbia (DC)

Boston, Massachusetts (MA)

El Paso, Texas (TX)

Nashville, Tennessee (TN)

Detroit, Michigan (MI)

Oklahoma City, Oklahoma (OK)

Portland, Oregon (OR)

Las Vegas, Nevada (NV)

Memphis, Tennessee (TN)

Louisville, Kentucky (KY)

Baltimore, Maryland (MD)

Milwaukee, Wisconsin (WI)

Albuquerque, New Mexico (NM)

Tucson, Arizona (AZ)

Fresno, California (CA)

Sacramento, California (CA)

Kansas City, Missouri (MO)

Atlanta, Georgia (GA)

Miami, Florida (FL)

Colorado Springs, Colorado (CO)

Raleigh, North Carolina (NC)

Omaha, Nebraska (NE)

Long Beach, California (CA)

Virginia Beach, Virginia (VA)

Oakland, California (CA)

Minneapolis, Minnesota (MN)

Tulsa, Oklahoma (OK)

Arlington, Texas (TX)

New Orleans, Louisiana (LA)

Wichita, Kansas (KS)

Cleveland, Ohio (OH)

Tampa, Florida (FL)

Bakersfield, California (CA)

Aurora, Colorado (CO)

Honolulu, Hawaii (HI)

Anaheim, California (CA)

Santa Ana, California (CA)

Corpus Christi, Texas (TX)

Riverside, California (CA)

Lexington, Kentucky (KY)

St. Louis, Missouri (MO)

Stockton, California (CA)

Pittsburgh, Pennsylvania (PA)

Saint Paul, Minnesota (MN)

Cincinnati, Ohio (OH)

Greensboro, North Carolina (NC)

Anchorage, Alaska (AK)

Plano, Texas (TX)

Lincoln, Nebraska (NE)

Orlando, Florida (FL)

Irvine, California (CA)

Newark, New Jersey (NJ)

Toledo, Ohio (OH)

Durham, North Carolina (NC)

Chula Vista, California (CA)

Fort Wayne, Indiana (IN)

Jersey City, New Jersey (NJ)

St. Petersburg, Florida (FL)

Laredo, Texas (TX)

Madison, Wisconsin (WI)

Chandler, Arizona (AZ)

Buffalo, New York (NY)

Lubbock, Texas (TX)

Scottsdale, Arizona (AZ)

Reno, Nevada (NV)

Glendale, Arizona (AZ)

Gilbert, Arizona (AZ)

Winston-Salem, North Carolina (NC)

North Las Vegas, Nevada (NV)

Norfolk, Virginia (VA)

Chesapeake, Virginia (VA)

Fremont, California (CA)

Garland, Texas (TX)

Richmond, Virginia (VA)

Baton Rouge, Louisiana (LA)

Boise, Idaho (ID)

San Bernardino, California (CA)

Spokane, Washington (WA)

Des Moines, Iowa (IA)

Modesto, California (CA)

Birmingham, Alabama (AL)

Tacoma, Washington (WA)

Fontana, California (CA)

Oxnard, California (CA)

Fayetteville, North Carolina (NC)

Huntsville, Alabama (AL)

Moreno Valley, California (CA)

Rochester, New York (NY)

Glendale, California (CA)

Yonkers, New York (NY)

Augusta, Georgia (GA)

Amarillo, Texas (TX)

Little Rock, Arkansas (AR)

Akron, Ohio (OH)

Shreveport, Louisiana (LA)

Grand Rapids, Michigan (MI)

Mobile, Alabama (AL)

Salt Lake City, Utah (UT)

Huntsville, Texas (TX)

Tallahassee, Florida (FL)

Overland Park, Kansas (KS)

Knoxville, Tennessee (TN)

Worcester, Massachusetts (MA)

Brownsville, Texas (TX)

New Port Richey, Florida (FL)

Jackson, Mississippi (MS)

Providence, Rhode Island (RI)

Fort Lauderdale, Florida (FL)

Sioux Falls, South Dakota (SD)

Tempe, Arizona (AZ)

Cape Coral, Florida (FL)

Springfield, Missouri (MO)

Pembroke Pines, Florida (FL)

Eugene, Oregon (OR)

Peoria, Arizona (AZ)

Corona, California (CA)

Lancaster, California (CA)

Rockford, Illinois (IL)

Salinas, California (CA)

Palmdale, California (CA)

Springfield, Massachusetts (MA)

Charleston, South Carolina (SC)

Duluth, Minnesota (MN)

London, England (ENG)

Dublin, Ireland (IRE)