Taycon AI deploys AI agents, workflow automation, and decision intelligence into the operations of Seattle and Puget Sound companies. Vancouver-headquartered, same time zone, and working remotely across the Pacific Northwest.
Same time zone (Pacific). Vancouver to Seattle is 230 km. Travel to Seattle available on a case-by-case basis. Same business day turnaround on async work.
Seattle is one of North America's deepest tech and SaaS markets. The companies that hire us want AI deployed into operations now, not another roadmap from a Big Four firm. Puget Sound SaaS scale-ups, eCommerce operators, logistics firms, and professional services practices all share the same starting point: a real operational problem that needs a working system.
Same time zone (Pacific) means we operate on your business hours with no lag. Vancouver to Seattle is a short flight or 2.5-hour drive so in-person kickoff is straightforward when it adds value.
Seattle SaaS companies automate customer support triage, success operations, and CRM enrichment at scale.
Puget Sound eCommerce operators automate demand forecasting, inventory intelligence, and customer operations.
Seattle and Puget Sound logistics firms automate warehouse reporting, supplier performance, and operational anomaly detection.
Seattle professional services firms automate document generation, client reporting, and billing workflows.
Pacific Northwest healthcare and biotech operations automate document intake, claims, and operational reporting.
Puget Sound manufacturers automate production reporting and operational intelligence.
Teams spending hours on data entry, report formatting, ticket sorting, and invoice follow-up. Tasks that follow predictable patterns and require no human judgment, but they consume people who should be doing higher-value work.
CRM, ERP, helpdesk, and data warehouse operating as silos. Data reconciled manually between them. Reports requiring exports, formatting, and re-entry before anyone can make a decision.
Leadership waiting on reports that take days to compile. Operational anomalies discovered during close instead of in real time. Forecasting built on spreadsheets updated once a month.
Support ticket volume growing faster than the team. Reporting workload increasing with every new system added. Processes that require more people every time the business grows.
Customer health scores built from gut feel instead of data. Pipeline accuracy dependent on reps remembering to update CRM. Operational performance visible only in retrospect.
Organizations that know AI can help but aren't sure which workflow to start with, what realistic outcomes look like, or how to build the internal case for an AI engagement.
AI consulting for customer operations focuses on support automation, CRM intelligence, and predictive success systems. AI triage agents classify and route tickets. CRM enrichment agents update records from call transcripts. Churn prediction models surface at-risk accounts before renewal conversations are too late.
AI for Customer Operations →AI consulting for business operations targets reporting pipelines, process automation, and operational anomaly detection. Monthly reports that take three days of manual work become same-day automated delivery. Cross-system data pipelines eliminate manual exports and re-entry. Anomalies surface automatically rather than during close.
AI for Business Operations →AI consulting for finance focuses on financial close automation, variance analysis, forecasting, and compliance monitoring. Quarterly close processes that take 12 days of manual handoffs are reduced to 4 days. Variance analysis is generated automatically from ERP actuals. Anomalies surface during the period instead of at close.
AI for Finance →We audit your operations and identify where AI creates the highest measurable impact. Every manual step, every system involved, every handoff between people and tools. You get a prioritized list of opportunities ranked by value and feasibility before we write a line of code.
We design the AI agents, automation pipelines, and decision models that fit your existing systems. The architecture is reviewed and approved before development begins. No surprises.
We build and deploy AI systems directly into your operational workflows. Parallel testing before go-live validates accuracy against real data. Zero disruption to your team during the transition.
We track performance against the baseline established in Discovery. Response times, error rates, time saved, and output quality are monitored. Models improve as the system learns from real operational data.
A 120-person management consulting firm was producing 40 to 60 proposals per month. Each one took two to three days of a senior consultant's time to research, draft, and format. The firm was winning work, but the proposal process was consuming capacity that should have been going to billable client delivery.
Taycon AI began with a two-week Discovery audit. We mapped the full proposal workflow: intake from the business development team, research from internal knowledge bases and past engagements, drafting, review, and formatting. We found that 70% of every proposal followed a predictable structure, with variable sections for industry context, proposed approach, and team credentials.
We designed an AI proposal generation system connected to their CRM, internal knowledge base, and past proposal library. When a new proposal is initiated, the system pulls relevant engagement history, industry context, and standard approach frameworks, and produces a first-draft proposal in the correct template. The senior consultant reviews, edits the variable sections, and approves.
Proposal production time dropped from two to three days to four to six hours. Senior consultants now spend their time on strategic positioning and client-specific insight rather than structure and formatting. The firm took on 30% more proposals in the same quarter without adding headcount.
We review your operations, identify your highest-value AI opportunity, and outline a practical path forward. Free, direct, and specific to your situation.
Small business: start with one workflow.
Mid-market: scale operations without adding headcount.
Enterprise division: deploy AI faster than your company-wide program allows.