rag × cross-enterprise

RAG systems for Cross-Enterprise.

Employees ask questions that cut across HR, IT, finance, and operations — and today they ask four different portals. We build unified retrieval-augmented generation that answers from every function's knowledge with a citation to the source-of-truth document, permission-aware so each person sees only what they are entitled to, and deployable on-prem.

On-prem option Permission-aware retrieval Cited to source-of-truth

One grounded answer across every function's knowledge

A large enterprise does not have one knowledge base — it has dozens, owned by different functions and locked behind different permissions. HR runs policies and benefits guides; IT runs runbooks and a ticketing knowledge base; finance runs procedures, controls, and expense policy; operations runs SOPs and playbooks. An employee's question rarely respects those boundaries, so people either bounce between portals or give up and ask a colleague.

We build a single retrieval layer over the whole estate. Each function's corpus is indexed with its own source-of-truth metadata, retrieval routes a question to the right body of knowledge, and reranking surfaces the passage that actually answers it — with the model constrained to cite the originating document. Permissions are enforced at retrieval, so one assistant serves every department without ever returning content a user is not entitled to, and the entire pipeline runs inside your environment.

Built for unified enterprise retrieval.

A retrieval layer engineered to span functions, route accurately, and enforce permissions across a multi-domain estate.

01 / ingestionCORE
Multi-domain document intelligence
We parse the content of every function — HR policies, IT runbooks, finance procedures, and operations SOPs — into structure-aware chunks tagged with domain, owner, source of truth, and version.
  • Per-function chunking
  • Domain & ownership metadata
  • Source-of-truth versioning
02 / retrievalSECURE
Permission-aware, routed retrieval
Retrieval routes each question to the right corpus, reranks the best passage, and enforces source-system permissions before anything reaches the model, with every answer cited — all inside your environment.
  • On-prem inference
  • Entitlement-scoped access
  • Source-cited answers
03 / corpusCORE
Cross-function corpus coverage
Coverage spans the breadth a multi-function enterprise runs on — HR, IT, finance, and operations knowledge — kept synced to each function's source-of-truth system with per-function evaluation.
  • HR & IT knowledge bases
  • Finance procedures & controls
  • Operations SOPs & playbooks

Where RAG unlocks value in the Cross-Enterprise

Value concentrates wherever a grounded answer exists in some function's knowledge but is too scattered across portals to retrieve quickly:

  • Employee self-service copilot — one assistant answers HR, IT, finance, and ops questions with a citation, instead of a tour of four intranets.
  • IT & helpdesk deflection — staff resolve common issues from the runbook or knowledge-base article directly, reducing ticket volume.
  • Policy & finance Q&A — employees confirm the current expense, travel, or HR policy from the controlling document, with the citation attached.
  • Onboarding & operations — new and cross-functional staff find the right SOP or playbook step across functions, with permissions honored at retrieval.

Common questions.

How does RAG enforce permissions across HR, IT, finance, and operations content?

Permissions are enforced at retrieval. The index carries each document's source-system access controls, and a query is filtered to the user's entitlements before anything reaches the model, so a single assistant can serve every function without a user ever seeing content they are not authorized for. The pipeline runs inside your environment, and every query and its sources are logged for audit.

How does one RAG system serve very different departments accurately?

We index each function's corpus with metadata that identifies its domain and source of truth, and retrieval routes a question to the right body of knowledge before reranking the best passages. The model answers only from what it retrieved and cites the originating policy, ticket article, or finance procedure, and we maintain per-function evaluation sets so accuracy is measured separately for HR, IT, finance, and operations rather than averaged into a single misleading number.

Explore related paths.

One assistant for the whole enterprise.

Bring a slice of two or three functions' knowledge and the questions your employees ask daily. In thirty minutes we will show how permission-aware, cited retrieval answers them on infrastructure you control. Response inside 24 hours.

Markets served.

As an enterprise AI agency, eeko systems delivers production AI systems 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)