DKK "On-Prem AI Operating System" Proposal
Turn 20 years of proprietary engineering know-how into a private, on-premise AI system that assembles contracts in minutes, enforces procedures, surfaces city/code criteria, and removes repeat questions from Derek's day.
DKK Consulting — Civil/Structural Engineering
Why DKK Benefits Now
Bottlenecked Expertise
Derek's brain is the system. Repeating guidance, stitching 200+ templates, and answering the same ops questions stalls throughput. Our private AI makes that knowledge usable by the whole team—on day one.
Manual Contract Assembly
Combining services (A/C/F) into a single CC takes too long and invites errors. The Contract Composer turns intake + checkboxes into one clean contract, fee table, records requests, and task list.
Agency/Code Sprawl
70–100 agencies, each with its own rules, portals, and criteria. Our Deep Research Agent attaches the latest city/building-code criteria to each job—no more hunting.
IP Must Stay Inside
Your life's work sits in your data center. We deploy entirely on-prem: local LLM inference, private vector store, zero cloud leakage.
Detailed Deliverables
Everything here maps to exactly what DKK asked for—delegation, time-to-perform, and analytics—while keeping all IP within your four walls.
DKK World — Private RAG
A retrieval system over your templates, SOPs, FAQs, exemplar plans, and Smartsheets. Answers are grounded with citations to the exact source (no "creative" AI).
Impact: fewer interruptions to Derek; repeat answers handled consistently.
Contract Composer (Multi-Service CC)
Select the services needed (e.g., Drainage + Survey + Geotech) and generate one contract with correct language, fee lines, records request, and API checklist.
Impact: contract build time cut from 60-90 minutes to just a few minutes.
Deep Research Agent (City/Code Criteria)
At intake, uses location to fetch and attach the current criteria (e.g., Boca Raton / Palm Beach County). Stores the snapshot to the job.
Impact: fewer reworks, faster submittals, consistent standards.
Procedure Builder (Playbooks → Tasks)
Service-specific procedures generate tasks, owners, checklists, and due dates (e.g., "Request Survey," "Pull Records," "Notify Subconsultant").
Impact: true delegation without relying on tribal memory.
Subconsultant Matcher (Optional)
Uses your referral data lake to suggest 2–3 appropriate subs with scope notes and auto-drafted bid requests.
Impact: faster bid cycles; standardizes outreach language.
KPI Dashboard (Smartsheets + DB)
Live tiles: contracts by division/city, cycle time, WIP, win rate, top CCs, best/worst performing jurisdictions, projections.
Impact: decisions without manual data pulls.
Security & Governance
On-prem Linux deployment, role-based access, per-action audit logs, versioned templates, staging → approval → production.
Impact: enterprise-grade security for your IP.
Change-Management Kit
Short videos + SOPs for the team; template versioning rules; "red banner" low-confidence warnings.
Impact: smooth team adoption and training.
Your Enterprise!
Enterprise-grade security with complete data sovereignty
On-Prem LLM
Local inference, no external API calls
Private Vector Store
Your data never leaves your infrastructure
Role-Based Access
Granular permissions and user controls
Audit Logs
Complete activity tracking and compliance
Zero Cloud Egress
100% contained within your four walls
How We'll Roll It Out
This isn't a 5-week sprint—it's a disciplined rollout to protect IP, quality, and adoption.
~10 weeks
On-prem kickoff, security review
Access, data map, template inventory, role matrix
RAG ingestion pipeline
First index of templates/SOPs; governance rules
Contract Composer build
Wireframes → build; merge logic for 3 services × 2 cities
MVP pilot with team
Accuracy fixes; citation enforcement; audit logs
Productionize
Backups, monitoring, training; sign-off
Caveat – Buffer Allowance
Engineering realities (template complexity, agency policy changes, security reviews, hardware lead times) may extend the plan. We set a 3–6 month buffer to absorb unforeseen dependencies while maintaining quality and IP protections.
Value Stack
Why this easily pays for itself: time and money you keep.
Contract Assembly Time
From 60–90 minutes → just a few minutes.
At ~400 contracts/year, that's 300–500+ hours back to the business annually.
Reduced Expert Interruptions
Grounded answers with citations handle repeat questions.
50–70% fewer interruptions to Derek.
Fewer Reworks & Faster Submittals
Criteria snapshots bound to location reduce back-and-forth.
Mistakes that stall permits are eliminated.
Standardized Procedures
Playbooks → tasks ensure nothing slips.
New team members ramp faster with less shadowing.
Decision Velocity
Live KPIs without manual pulls.
Know best/worst cities, contract mix, cycle time, and WIP instantly.
IP Protection
100% on-prem; zero cloud egress.
Your life's work stays inside your four walls.
Phases
Phased Packages Only
Items delivered inside of each phase are subject to change based on project and workflows, but the overall scope of the entire project will be delivered.
Essential foundation for your AI operating system
Operational efficiency and automation tools
Advanced features and ongoing support
Post-Launch Stewardship
Your AI system is local and private—but it isn't static. Models, templates, and city criteria change. Stewardship keeps everything fast, safe, and correct without adding headcount.
24/7 health checks on LLM, embeddings, vector DB, GPUs, latency, disk; alerting & incident playbooks; verified backups and restore tests.
Safe upgrades to model/runtime (vLLM/TGI, CUDA/driver), embedding & reranker refresh cadence, drift checks, regression suite before releases.
PR/approval workflow for clauses, versioning & rollback, RAG quality audits with sampled Q&A and citation accuracy.
RBAC updates (joiners/leavers), credential rotation, CVE patching, TLS/cert renewals, egress attestations, monthly audit report.
Up to 12 engineering hours/month for minor improvements (new merge rules, KPI tiles, small UI fields), 1 production release/month; quarterly DR exercise.
If a driver breaks GPU, a vector index corrupts, or a template refactor misaligns embeddings—we own the fix under SLA.
Business Case in One Line
This replaces ~0.4–0.6 FTE across DevOps + MLOps + DataOps with an SLA'd team for $2.5k/mo— far less than hiring, and cheaper than a single day of outage or rework.
Guaranteed Success Metrics
Measurable, Relevant, Auditable
Target:
Multi-service CC generated in a few minutes (median)
Measured by:
Composer logs (start → signed draft)
Target:
≥90% of eligible contracts generated via Composer by 4 weeks after launch
Measured by:
% of contracts initiated through Composer vs. manual
Target:
≥95% of AI answers cite approved sources; ≤2% flagged low-confidence without human review
Measured by:
RAG audit sampling & confidence thresholds
Target:
100% of new jobs have a location-bound criteria snapshot attached
Measured by:
Job record checks
Target:
≥99.5% service uptime (business hours) after Phase I go-live
Measured by:
Monitoring/alerting reports
Target:
50–70% fewer repeat-answer interruptions to Derek by week 18
Measured by:
Ticket tagging / interruption log
Accountability Promise
All metrics are tracked on an internal dashboard and reviewed in monthly stewardship reports. We stand behind these targets with measurable, auditable results. If we fall short on delievery, we work for free till agreed upon delieverables are deployed.