westridge.io
GenAI · Agentic AI · Automation

We build AI that works
for your business. Today.

From agentic AI and workflow automation to intelligent document processing — end-to-end delivery for mid-market companies ready to move fast.

3 days
To a fixed-price quote
3 weeks
To production
3 months
Support & tuning included
Client owns
All IP
What we do

Three AI practice areas.
One accountable owner.

We don't hand you a strategy deck. We architect, build, and deploy — then stay accountable to the outcome.

GenAI
GenAI Integration
Custom AI assistants, data/RAG pipelines, and document intelligence — grounded in your data and integrated into your existing workflows.
OpenAIAnthropic ClaudeGeminiRAG
Agentic AI
Agentic AI
AI agents that reason and act autonomously across multi-step tasks — with the human oversight gates you define.
LangChainCrewAIAutoGenMulti-agent
Automation
Workflow Automation
Business processes that run themselves on N8N — CRM, finance, HR, and ops workflows without human intervention.
N8NAPI integrationCRMAI-enhanced
AI Readiness Assessment
Know exactly where to invest before you commit to a budget.
A scored, structured report — not a strategy deck. Fixed price, fixed scope.
Request assessment →
30-min scoping call · No commitment required
Technology

Built on the platforms that matter.

AI · Automation
AI · LLM
Anthropic Claude
Claude Partner Network member. Primary LLM for production AI systems.
AI · LLM
OpenAI
GPT-4o for multimodal and API-first GenAI integrations.
Automation
N8N
Core workflow orchestration platform for all automation engagements.
Agentic AI
LangChain
Agent framework for multi-step reasoning and tool use.
Cloud · Infrastructure
Cloud
AWS
Migration, managed services, and Bedrock AI workloads.
Cloud
Microsoft Azure
Azure AI, Government Cloud, and enterprise migration.
Cloud
Google Cloud
Vertex AI, GKE, and data platform modernization.
Frontend
Next.js · Vercel
Web and AI product delivery. This site runs on Next.js.
Why this is different

Most AI tools guess.
Ours tells you what it doesn't know.

The hardest question a regulated buyer asks is not what the system can answer — it is what happens when it cannot.

01
Compile, then embed

We compile your documents into a structured, versioned wiki before indexing — not raw chunks. Retrieval quality in messy real-world document sets is materially better.

02
STRICT mode with citations

Every answer carries an inline source. If the wiki can't support an answer, the system says so and logs a knowledge gap.

03
Human gates, full audit trail

Every action is logged with timestamp and context. High-impact actions require explicit approval.

04
Your infrastructure, your data

Dedicated single-tenant deployment. Your wiki lives in your GitHub. Exportable at any time.

How we compare

Most AI projects never ship.
Ours start at $5,000 and take three weeks.

S&P Global found that the average organization scrapped 46% of its AI proofs-of-concept before production. In 2025, 42% of firms abandoned most of their AI initiatives outright — up from 17% a year earlier. The obstacle is rarely the technology. It is an engagement model that bills for months before anything runs.

WestridgeHire in-houseSpecialist AI firmLarge consultancy
What it costs to start$5,000$205K–$330K a year, fully loaded$25K–$50K for a scoped POCQuoted time and materials
Time to something running3 weeks6–12 months, including the hire2–6 monthsMulti-month programs
Who does the workOne senior architectYour first AI hireA team of 1–5Partner-track pyramid, blended rates
What you are left holdingPlain markdown in your own repoWhatever they built, if they stayDeliverables yours; methodology retainedDeliverables yours; platform retained
One architect, not a bench — and we will say so

You get continuity of thinking and a single accountable owner, not a rotating team. The trade-off is real: there is no bench behind us. That’s why every artifact is plain text in your own repository, readable and maintainable without us.

The hyperscalers point firms your size elsewhere

AWS states its Professional Services arm is best positioned for large programs of work, and directs smaller buyers to partners. Microsoft runs a separate SMB partner channel rather than delivering directly. Companies under 500 people are not their model.

Why the numbers differ this much

Not a discount. One senior architect with an AI-augmented delivery stack ships what used to need a team, so the cost base is structurally lower. The saving shows up in your price, not in our margin.

In-house cost derived from US Bureau of Labor Statistics OEWS wage data and the BLS Employer Costs for Employee Compensation benefits load. Project abandonment figures from S&P Global (survey of 1,000+ enterprises). Consultancy cost ranges reflect published rate cards, including UK G-Cloud and US GSA schedules. Large-consultancy engagements are quoted time and materials; no public minimum is published. Hyperscaler engagements may be partly co-funded through programs such as AWS MAP, which narrows the gap on cloud work.

Who we serve

Two industries.
One problem we
know how to solve.

We work with owner-operated and mid-market businesses — 10 to 500 employees. Every engagement starts with a specific industry pain, not a technology pitch.

Financial Services · RIAs · Wealth Management
Compliance knowledge locked in files no one can find
  • Advisors spending 20+ minutes locating a single policy
  • New staff can't find answers without asking a senior person
  • Compliance prep means hunting through dozens of documents
Illustrative scenario

If you're a 40-person RIA whose ADV, policies and SOPs live across a shared drive and three inboxes, this is the engagement that makes the whole corpus answerable in plain English — with a citation on every answer.

Start with a bounded pilot over 50 documents — Knowledge Starter
Professional Services · Accounting · Law · Consulting
Billable hours lost to searching instead of advising
  • The same contracts, policies and SOPs searched manually every week
  • Junior staff blocked waiting on a senior person for answers
  • Institutional knowledge walking out the door with turnover
Illustrative scenario

If you're a practice where three partners are the only people who know where anything is, this is the engagement that turns that knowledge into a queryable layer — one that abstains rather than guessing when a source is missing.

Scale it across your whole knowledge base — Knowledge Engine

Not your industry? The patterns repeat — book a scoping call and we'll tell you if there's a fit.

Ready to find out where AI moves the needle for you?

Start with the AI Readiness Assessment. A clear plan in 3 weeks. No guesswork, no vague roadmaps.