Pylon AI

Solutions

Packaged AI solutions built for enterprise operating realities.

Where services describe how we work, solutions describe what we deliver. Each Pylon AI solution is a proven pattern — a structured engagement with defined inputs, outputs, and measurable outcomes — designed around the problems enterprises actually face.

Adoption Program

AI Adoption Program

Most enterprises have a hundred AI ideas and no clear path to their first ten production deployments. The AI Adoption Program provides the strategy, architecture, and initial delivery structure to convert AI ambition into an operating program with measurable momentum.

This is typically a 90–180 day engagement that ends with at least two AI systems in production, a governance framework, a prioritized roadmap, and an internal team capable of continuing the work.

Start your adoption program

What you get

  • AI maturity assessment and gap analysis
  • Use-case portfolio: scored, sequenced, and resourced
  • Architecture blueprint for the first two production systems
  • Governance and policy framework
  • Two production AI deployments with full knowledge transfer
  • Ongoing roadmap and internal AI capability assessment

Typical outcomes

First production AI system operational within 60 days. Internal AI team with defined roles and a repeatable delivery pattern. CFO-ready ROI measurement from day one of deployment.

Knowledge Systems

Enterprise Copilots

An enterprise copilot is an AI system that works alongside your employees to answer questions, surface information, complete tasks, and accelerate decisions — grounded in your company's data, policy, and context. Done right, they reduce time-to-answer from hours to seconds and make every employee more effective.

Pylon AI designs and builds production-grade copilots for internal operations, customer-facing roles, and technical teams — secured, governed, and observable from launch.

Build your copilot

What you get

  • RAG-based knowledge system grounded in your enterprise data
  • Multi-source retrieval: documents, databases, APIs, and knowledge bases
  • Access-controlled responses: employees see only what they should
  • Tool integration: calendar, CRM, ticketing, and internal systems
  • Citation and source attribution for every response
  • Evaluation framework: response quality, hallucination rate, user satisfaction

Typical outcomes

50–80% reduction in time employees spend searching for internal information. Measurable improvement in response quality for customer-facing roles. Onboarding time reduction for new hires.

Workflow Automation

Agentic Workflows

The transition from AI that answers to AI that acts is where the largest enterprise value is created. Agentic workflows automate complex, multi-step processes that previously required significant human coordination: research and synthesis, data gathering and analysis, document processing, approval routing, and cross-system orchestration.

We design and build agentic systems using LangGraph, CrewAI, AutoGen, and custom MCP-based orchestration — with human-in-the-loop controls, state management, and full observability.

Design your agentic workflow

What you get

  • Agent architecture design for your specific workflow
  • Tool and API integration: CRM, ERP, databases, web services
  • Human-in-the-loop approval and escalation patterns
  • State management and workflow recovery
  • Monitoring, alerting, and audit trail
  • Cost and usage controls to prevent runaway agent costs

Typical outcomes

60–90% reduction in human time for targeted workflow categories. Error rate reduction through consistent process execution. Hours-to-minutes cycle time compression for multi-step processes.

Model Infrastructure

Multi-Model Platforms

A single model is rarely the right answer for an enterprise AI portfolio. Different tasks demand different cost, quality, and latency profiles. Enterprises that commit to a single vendor expose themselves to pricing leverage, capability gaps, and single points of failure.

We design and build model-agnostic inference platforms that route requests intelligently across OpenAI, Anthropic, Google, AWS Bedrock, and open-weight models — with unified observability, cost controls, and a single developer interface.

Design your model platform

What you get

  • Unified API gateway abstracting model provider differences
  • Intelligent routing: cost-based, quality-based, and latency-based
  • Fallback and redundancy logic across providers
  • Unified observability: cost, latency, quality, and usage across all models
  • Rate limit management and request queuing
  • Prompt versioning and A/B testing infrastructure

Typical outcomes

30–60% reduction in inference costs through intelligent routing. Zero vendor lock-in. Single observability plane across all AI spend and usage.

Cost Control

AI Cost Optimization

Enterprise AI spend is growing faster than outcomes justify for many organizations. Token costs, compute bills, and infrastructure spending are rising without clear attribution to business value. Unchecked, this creates a CFO problem that puts entire AI programs at risk.

We audit your AI spend, identify optimization opportunities, and implement cost reduction measures — typically achieving 30–70% cost reduction without sacrificing quality or capability.

Audit your AI costs

What you get

  • Full AI cost audit: token spend, compute, storage, and tooling
  • Cost attribution by application, team, and use case
  • Prompt optimization to reduce token consumption without quality loss
  • Model right-sizing: using cheaper models where appropriate
  • Caching strategy for frequently repeated requests
  • Cost-per-work-unit measurement framework
  • Budget controls and alerting implementation

Typical outcomes

30–70% reduction in AI inference costs. Full visibility into AI spend by team, application, and use case. CFO-ready cost-per-work-unit reporting for every AI system.

Risk, Governance & Security

AI Governance & Security Framework

AI systems deployed without governance and security controls create regulatory exposure, reputational risk, data leakage, and agentic abuse pathways. As AI becomes critical infrastructure, the absence of policy, observability, threat modeling, and runtime controls is not an oversight — it is a liability.

We build governance and AI security frameworks from day one to satisfy legal, compliance, risk, and CISO requirements while enabling the enterprise to move fast. Controls that slow everything down are poorly designed; ours are built into the architecture for SOC 2 readiness, HIPAA-aligned controls where applicable, auditability, and regulated operating environments.

Build your AI governance and security posture

What you get

  • Day-one secure-by-design operating model for enterprise AI adoption
  • AI use policy: acceptable use, prohibited use, and review processes
  • Model and system inventory with risk classification
  • Guardrail implementation: content filtering, PII detection, hallucination controls
  • AI threat modeling aligned to OWASP LLM, OWASP MCP, and MITRE ATLAS
  • Prompt injection, data exfiltration, tool abuse, and excessive agency controls
  • Audit trail and logging for regulatory compliance
  • Bias and fairness assessment for high-stakes use cases
  • AI risk register and escalation procedures
  • SOC 2 readiness, HIPAA-aligned control mapping where applicable, EU AI Act, and emerging regulatory readiness assessment

Typical outcomes

Board-ready AI governance and security posture. Legal, compliance, and security sign-off on AI systems. Reduced incident rate and faster incident response. Regulatory readiness for AI governance frameworks including EU AI Act.

Value Measurement

AI ROI & Outcomes Tracking

Most enterprises cannot answer a simple question: what is our AI investment actually returning? Token bills and compute costs are visible, but business outcomes—time saved, error rates reduced, revenue influenced, decisions accelerated—are scattered across teams with no unified view. When the CFO asks, nobody has a number.

We design and instrument an outcomes tracking layer across your AI portfolio—linking every AI system to the business metric it is meant to move, capturing before-and-after baselines, and surfacing ROI in language your executive team and board can act on.

Build your ROI framework

What you get

  • Outcomes inventory: every AI system mapped to its business KPI
  • Baseline capture before deployment so delta is measurable
  • Live ROI dashboard: cost-per-unit-of-work, time saved, error reduction
  • Attribution model linking AI activity to revenue, cost, and risk metrics
  • Benefit realization reporting cadence for executive and board audiences
  • Anomaly detection when a system’s value drifts or degrades
  • Portfolio view: which AI investments are paying off, which to scale or kill

Typical outcomes

CFO and board-ready ROI reporting within 60 days. Clear visibility into which AI systems are delivering and which are underperforming. Confident investment decisions for the next AI budget cycle backed by production data, not projections.

Tell us your situation. We'll recommend the right starting point.

Most engagements start with a 30-minute call where we understand your priorities, constraints, and timeline — and give you an honest view of what makes sense.

Schedule a Discovery Call View All Services