Agentic Systems for B2B Teams

Your highest paid people lose two hours a day hunting for answers.

This Information Tax eats directly into margins and delays execution. We engineer custom internal systems that consolidate scattered records into unified, actionable context. Built on your infrastructure. Designed for execution.

Agentic AI built for execution, not just conversation
Infrastructure Audit - $500
Fragmented knowledge
Manual workflows
Tool sprawl
Compliance / risk
Try the live demo

$500 fee (credited) • 45 - 60 min session • Technical Plan delivered

Principal led, no junior staff Private deployment in your cloud Fixed price build, no hourly surprises
[ ENGINE_LIVE: STRIPE_V3 ]
v3.0.42_STABLE
[14:22:01] > INITIALIZING_VECTOR_SEARCH...
[14:22:02] > ANALYZING_IDEMPOTENCY_KEYS...
[14:22:03] > SYNTHESIZING_ARCHITECTURE_SPEC...
"For multi-party payouts in Stripe Connect, use Account Tokens for KYC-less onboarding layers while maintaining split-fee logic in the Transfer API..."
// TECHNICAL_PROOF

Stop imagining AI.
Start deploying systems.

We don't build "chatbots." We build high-throughput intelligence layers that reason across your live documentation and data corpus with provable precision and zero-guess integrity.

EXPLORE_THE_DEMO ()

Austin Sector Fragility: The Mid-Market Tax

We target the surgical ops-heavy goldmines where Austin mid-market firms (20-80 employees) reach an operational ceiling. These are the "broken links" in your information chain.

[SEC_ID: PROPTECH]

Document Stacking Bottleneck

Manual review of 400-page loan files (W-2s, bank statements, CDs) into logical bundles. 10-15% defect rates in "stacking" lead to underwriting latency and audit risk.

The Fix: Distributed ingestion pipelines (Ray/Docling) that automate document classification and ROI verification with 90%+ hit rates.
[SEC_ID: LOGISTICS]

The "Human Router" Friction

Information silos between estimators and installation crews. Data "leaks" from site specs to iron fabrication, leading to material miscounts and installation delays.

The Fix: Real-time "Capital Systems" that act as a single source of truth for field documentation, using RAG to bridge the estimator-to-crew gap.
[SEC_ID: B2B_SAAS]

The Ingestion Bottleneck

Massive log data or unstructured dark web sourcing breaks traditional ETL. Scalability leads to "Semantic Drift" and latency jumps of up to 40% in RAG retrieval.

The Fix: Advanced partitioning and metadata filtering that handle multimodal complexity without sacrificing real-time freshness.
Live_System_Active

RAG engine turns Stripe API docs into architecture in 8.2s.

ENTER_COMMAND_CENTER
[ DIAGNOSTIC_AUDIT ]

Quantify the Information Tax.

Use the tactical calculator below to determine the precise annual EBITDA drag caused by manual retrieval and context fragmentation.

10 hrs

// MEASURED_PER_RELEVANT_HEAD

$55/hr

// INCLUDES_1.3X_LABOR_BURDEN

Burden Multiplier 1.3x
Effective Hourly Cost $72/hr
Operational Latency 520 hrs
EBITDA_DRAIN_TOTAL
-$37,180
INITIATE_RECOVERY_PROTOCOL ()
[02] ARCHITECTURAL_SCALE_OUT_PROTOCOL

HNSW / IVFFlat Indexing

We deploy disk-optimized Hierarchical Navigable Small World indexes via pgvectorscale for 10x retrieval speed at 99.9% recall on billion-vector sets.

64-Core SSD RAID 10

High-concurrency query execution spanning 64-core threads with NVMe RAID arrays delivering >1M IOPS for disk-heavy searching.

Citus Table Sharding

Horizontal sharding across distributed Postgres nodes for 10TB+ corpora. Read replicas scale search throughput from 400 to 4,000+ QPS.

Faithfulness Trace

Every response is grounded in semantic retrieval trace. We deploy RAGAS-level observability to prevent hallucinations and maintain 100% data integrity.

// SYSTEM_INTEGRITY: OPTIMIZED_FOR_BEYOND_DEMO_STATE

ENGINEERING STRATEGY: BUILT ON YOUR STACK, NOT OURS.

Vertex AI
OpenAI
Anthropic
Gemini
Azure OpenAI
Supabase
pgvector
Pinecone
LangChain
Slack
Vercel
Stripe
Clerk
FastAPI
HubSpot
n8n
Python
Docker
[PREPARATION_LAYER]

What You Need for the Audit

  • One Workflow: A concrete loop where people constantly hunt for information.
  • One Real Example: A live ticket, job, or deal you can pull up on screen.
  • Access: Ability to screen‑share the tools that hold that data (CRM, Drive, etc.).
  • Decision Maker: Someone on the call who can speak for budget and environment access.

How the Infrastructure Audit & Capital Sprint Works

A 3-step process to quantify your opportunity and demonstrate immediate asset value.

01

Intake + Walkthrough (Day 0-1)

We map exactly where your high-leverage people are hunting for answers or doing manual glue work. We build on your stack, not ours.

02

Tax Map + System Design (Day 1-3)

I quantify the Information Tax and design the Capital System to remove it. You see the "Future State" architecture before we build.

[MATH_OF_EBITDA_RECOVERY]
ROI = (Cmanual × Erate) - (Cai + Coversight)
// C_MANUAL: Fully Burdened Labor Cost
// E_RATE: Documentation Error Rate (10-15% Baseline)
// C_OVERSIGHT: Human-in-the-loop Validation cost
03

Targeted Systems Launch (2-4 Weeks)

We build the production-ready retrieval system wired into your CRM, document stores, and field apps. We demonstrate immediate EBITDA recovery through private AI engines deployed in your cloud.

The "Bold Experiment" Example

How we think: Structural changes, not just better colors.

The Proposal

"Stop passing permit PDFs around in email. Move to a live job record where permit requirements, status, and documents are all attached to the work order."

Why it works (Systems Thinking)

  • Data Integrity: One source of truth instead of conflicting versions in inboxes.
  • Speed: Crews see exactly what’s approved and what’s missing without asking ops.
  • Result: Fewer delays, less rework, measurable drop in Field Ops Information Tax.
[SYSTEM_MODES]

CHOOSE YOUR INFRASTRUCTURE DEPTH

A breakdown of the three primary modes of intelligence we deploy.

[SYS_ID: 0x01_RAG]

Retrieval Systems

Target: Crews & Operators

Focus on 'Instant Answers' and eliminating document hunting. Embed retrieval into existing tools so teams pull specs in seconds instead of searching PDFs.

THE_FIX: Cuts time-to-answer by 60-80% through context-aware document synthesis.
[SYS_ID: 0x02_SIGNAL]

Signal Systems

Target: Managers

Focus on 'Clean Signal' and aggregating CRM, Billing, and Ops. Turn fragmented data into a single autonomous briefing for management.

THE_FIX: Keeps leadership in exception-only mode, increasing span of control.
[SYS_ID: 0x03_LOOP]

Automation Loops

Target: Founders & Admins

Focus on 'Operational Velocity' and automating the contract-to-onboarding flow. Reclaim senior leadership's time by engineering out glue work.

THE_FIX: Moves senior staff off $20/hr work and into scaling decisions.

Why Replace Scripts with Capital Systems?

01
Asset Construction, Not Duct Tape.

I build permanent data pipelines and retrieval graphs that compound over time, replacing fragile no-code setups.

02
Fixed-Scope Deployments.

We start with a targeted $4,000–$8,000 sprint to wire a production loop to your specific CRM and document systems. No open-ended billing.

03
Principal Engineering Level.

You work directly with an architect designing around system risk, controls, and deployment realities, not a junior developer testing generic AI prompts on your data.

README.md

Technical Documentation

> Q: What AI infrastructure do you build on?
// A: We build on your stack, including Vertex AI, OpenAI/Azure, Anthropic, Gemini, or Postgres with pgvector. We use the right LLM for each job behind a stable API layer so you're never locked to a single model vendor (so you can swap models without breaking internal clients).
> Q: What exactly do we get in a Capital Sprint?
// A: You get a 2-4 week build of one high-impact internal system wired into your live tools (CRM, Drive, field apps). Data is semantically indexed into a private vector index served via Slack or internal UI.
> Q: How do you handle security and data isolation?
// A: We deploy logically isolated environments (VPCs) on major clouds. Your documents are never used to train public models. Every answer includes citations, and the system is engineered to say "I don't know" rather than hallucinate. Audit-friendly logging of queries and data access is available.
> Q: Are we locked into you or a specific vendor?
// A: No. You own your data and vector index. Our architecture is built on open standards. We do not run a proprietary SaaS and you can move between vendors without rewriting everything. We design and deploy the Capital System, we don't lock your IP in a black box.