Turn scattered tools into one operating layer.Production Claude Implementation and AI Pilot Rescue

    TechTide AI connects the tools your business already owns.

    Your CRM, billing, support, docs, spreadsheets, inboxes, and AI tools stop being separate tabs to chase. They become one operating layer your team can query, act on, and trust. No rip and replace. Start with a $1,000 Workflow Intelligence Audit that names the highest-leverage question you should be answering, and the first build path to answer it.

    Stuck Claude pilot? Talk to a Claude implementation consultant →

    Columbus, OH · Founder & CTO, TechTide AI · 13 years of mixed IT · Lovable Champion · Completed 9 Anthropic Academy courses

    [ FREE, DELIVERED IN 24 HOURS ]

    Get the AI Production Readiness Checklist

    The same 24-point checklist we run during a $1,000 AI Audit. Evals, guardrails, MCP scope, observability, cost ceilings. Plus the Automation Vibes weekly drop on shipping Claude in production.

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    Answer expensive workflow questions without chasing tabs. No rip and replace.

    Book the Workflow Intelligence Audit — $1,000 →See the offer ladder
    Need a speaker? alexcinovoj.comJoin Automation Vibes

    [ THE OPERATING LAYER ]

    One layer over the tools you already own.

    Your business already runs on CRM, billing, support, docs, spreadsheets, inboxes, and a growing pile of AI tools. Each one holds part of the answer. None of them talk to each other well enough for your team to stop tab-hopping.

    TechTide AI wires those systems into one operating layer. Your team asks a workflow question in one place and gets a grounded answer, or takes an action, without opening seven tabs. No rip and replace of the systems that already work.

    CRMBillingSupportDocsSpreadsheetsInboxesAI toolsOPERATINGLAYERTechTide AITeam

    [ QUESTIONS YOU CAN'T ANSWER TODAY ]

    The workflow questions your team keeps deferring.

    Every one of these questions requires stitching together data that already exists inside your business. The operating layer is what makes them answerable in seconds instead of a two-week ad-hoc analysis.

    • [ ? ]

      Which accounts are silently churning right now, based on billing, support, and product-usage signals together?

    • [ ? ]

      What is our real cost-to-serve per customer once you include support tickets, AI tokens, and infrastructure?

    • [ ? ]

      Where is revenue leaking between the CRM opportunity, the signed contract, and the invoice actually sent?

    • [ ? ]

      Which workflows are consuming the most human hours this month, and which of them would be safe to hand to an assistant?

    • [ ? ]

      What did we tell this customer over the last 90 days across email, support, docs, and calls, in one summary?

    • [ ? ]

      Which vendors are we paying for capabilities we already have inside another tool we already own?

    [ OFFER LADDER ]

    Audit. Sprint. Retainer.

    A paid front door, an obvious next step, and a durable expansion after proof. The retainer is not the first ask; the audit is. Each tier has a written scope, a named price, and a clear promise.

    [ TIER 1 · PAID FRONT DOOR ]

    Workflow Intelligence Audit

    $1,000 · 1 week

    Sells clarity plus the first build path. We map the tools you already own, the workflow questions your team keeps deferring, and the highest-leverage question to answer first. You leave with a written audit and a scoped first build path — not a strategy deck.

    • · System map of the tools already in play.
    • · Shortlist of workflow questions ranked by cost of not answering.
    • · One highest-leverage question named as the first build target.
    • · Scoped Data Spine Sprint proposal, priced and timelined.
    Book the Audit — $1,000 →
    Obvious next step

    [ TIER 2 · FIRST BUILD ]

    Data Spine Sprint

    $5,000–$7,500 · 2–3 weeks

    Sells the first working connected view. We wire the highest-leverage question end to end: the source tools, the connectors, and the single surface your team queries. Real answers on real data, not a demo.

    • · Connectors into the specific systems the audit named.
    • · One connected view answering the target question on live data.
    • · Access controls scoped to who should see what.
    • · Handoff runbook so your team can extend it.

    [ TIER 3 · DURABLE EXPANSION ]

    Operating Layer Retainer

    $15,000 / month · after proof

    Sells the durable operating layer. After the first sprint proves the pattern, we extend the layer across the rest of the business: more workflow questions, more connectors, ongoing hardening, and monthly review of what to build next. Not the first ask.

    • · Additional workflow questions shipped each month.
    • · Ongoing connector maintenance and access review.
    • · Monthly written work plan; no open-ended scope.
    • · Pair-programming with your engineers so ownership stays in-house.

    No rip and replace · Fixed scope · Named price · Written outcome

    [ WHO THIS IS FOR ]

    Three kinds of buyers. One operating layer.

    The offer ladder fits the same shape of problem in three different business contexts. If you see yourself here, the Workflow Intelligence Audit is the entry point.

    [ ENTERPRISE ]

    AI, IT, product, and data leaders

    You already own the systems. The board is asking why the workflow questions still take two weeks to answer, and why the AI budget is not showing up in the P&L. You need a connected view before you spend another quarter on point tools.

    [ HEARTLAND OPERATOR ]

    Local and Heartland operators

    Multi-location services, distribution, ops-heavy businesses in the Midwest. Your team runs on QuickBooks, ServiceTitan or equivalent, email, spreadsheets, and a shop-floor app. You want the same answer your enterprise counterparts get, without hiring a data team.

    [ AGENCY / OPERATOR ]

    Agencies, content, and service operators

    You bill for outcomes. Your team lives in Notion, Airtable, HubSpot, Slack, and a stack of AI tools. You need one place your operators can query client work, capacity, and margin without stitching exports together every Monday morning.

    Recognition and proof

    Favikon · Top 5 AI EducationCo-founder · FigGlow.ai57K LinkedIn followers

    Stack we ship on

    AnthropicClaude CodeMCPLovableSupabasen8nPythonTypeScriptReactTailwindVite

    [ OFFER ARCHITECTURE ]

    Audit. Triage. Rescue. Fractional FDE.

    Each offer comes with proof you can verify. See how we did this on Stripe Connect and Intune rollouts in the Case Files, read the 13-year operator Ledger of verified projects with hard numbers, or skim the voice rules in the Anti-Hype Manifesto.

    [ Decision gate ]

    AI Production Readiness Audit

    $1,000 · 48 hours

    Who: Founders, CTOs, and AI or product leaders who need a clear answer before spending another month or dollar on an AI initiative.

    In scope: 90-minute live review of your AI workflows, agents, MCP tools, retrieval, permissions, evals, costs, and observability. Written deliverable within 48 hours with a clear go/no-go decision, the biggest risks called out by name, and a ranked action plan your team can follow.

    Out of scope: No vague strategy deck. No 40-page report. No production code written during the audit window.

    Outcome: A clear next step in 48 hours: fix it internally, book an implementation sprint, or kill the initiative. Just the decision, the risks, and what to do next.

    Reserve, $1,000

    [ Qualification gate ]

    Production Triage

    $5,000 · 7 days

    Who: Engineering leaders and AI task-force owners whose Claude pilot is stuck between demo-good and production-ready, three weeks from a deadline or six months past one.

    In scope: Seven-day architecture review of the existing pilot: code, prompts, MCP servers, retrieval, evals, observability. Permission and token-spend audit on every MCP integration. Written triage report and sequenced 21-day fix list.

    Out of scope: We do not write production code, run vendor-selection theater, or produce strategy decks. Onboarding new team members is out of scope.

    Outcome: A go/no-go call on whether this pilot is worth shipping, delivered in seven days. We rescue the half worth saving and refuse the rest.

    Scope

    [ Production path ]

    Workflow Rescue

    $25,000, $40,000 · 21 days

    Who: Teams that finished Production Triage with a green light, or teams already convinced their pilot is salvageable and ready to skip straight to build.

    In scope: Fixed-scope 21-day production deployment of one stuck workflow: hardened MCP integrations with scoped permissions, regression eval suite, observability wired to your stack, runbook, and pair-programming handoff to the owning engineer.

    Out of scope: A second workflow is a second Rescue. Long-tail maintenance retainer is Fractional FDE. Org-design and change-management consulting are out of scope.

    Outcome: One workflow running in production with logs, dashboards, and your engineers trained to extend it. Failure mode named: scope creep is the failure mode, and we hold the line on the 21-day fixed scope.

    Scope

    [ Long-term engagement ]

    Fractional FDE

    $25,000, $40,000 / month · 3-month minimum

    Who: CTOs and AI task-force owners who need ongoing senior AI implementation muscle without a full-time hire. Best after one or two successful Rescues.

    In scope: Three-month minimum embed: weekly pair programming, design reviews, MCP and Claude Code training, two to three additional production workflows, written standards docs, hiring-loop support, direct Slack access during business hours.

    Out of scope: Not on-call coverage, not 24/7 production support, not a replacement for your CTO or head of engineering. Each month has a written work plan to prevent open-ended scope creep.

    Outcome: Senior in-house AI capability, not dependency. Up to three production workflows shipped over the engagement, with your engineers owning them at the end.

    Scope

    [ CASE FILES ]

    Shipped. Sanitized. On the record.

    Every velocity claim names the failure mode in the same paragraph. Architecture diagrams, Looms, and arXiv references live inside the file, not on the marketing page.

    • [ PAYMENTS PLATFORM ]

      Production concurrency controls · 14-day core migration

      Core API migration in 14 days, full rollout in 4 weeks

      A mid-market SaaS on Stripe v1 needed to move to Stripe Connect v2 before a payout cutover. We delivered the core API migration in 14 days under a dual-API webhook coexistence pattern: v1 writes were shadow-replayed against v2 entities, with reconciliation jobs catching drift inside the same nightly window. Full rollout completed in 4 weeks once finance signed off on the reconciliation report. The implementation utilizes production concurrency controls for nightly Stripe reconciliation across the multi-entity ledger. Failure mode named in the runbook: Stripe rate-limit ceiling caps throughput when entity count exceeds approximately 120, mitigated by a backoff schedule and an alert that escalates after two consecutive misses. The architecture diagram and Loom walkthrough live inside the case file.

      Open the case file

    01 / 05

    Open the full library

    [ CAPABILITIES ]

    What we build, and what we refuse to build.

    Six capability surfaces. Each one ships with a named failure mode, an eval, and a runbook.

    • MCP server development

      We build production MCP servers: scoped OAuth, typed tools, rate limiting, audit logging, and output validation on every response. Two production MCP servers shipped to date, both running under read-mostly scopes with explicit write-confirmation gates. Failure mode named: MCP transport latency under high concurrency is the dominant tail-latency contributor, mitigated by tool-level timeouts and a circuit breaker that fails the agent loop cleanly rather than hanging. Patterns lift directly into your existing observability stack. The handoff package includes a deployment runbook, an eval suite, and a written threat model.

    01 / 06

    [ PROOF ]

    Operator notes, public recognitions, telemetry.

    Operator quotes from sanitized engagements are marked anonymized in the schema. Public recognitions are named. No fabricated testimonials.

    • Operator note

      Took us from a Stripe v1 lock-in we had been postponing for a year to a working v2 core in 14 days, with a written rollout plan to finish in 4 weeks. The dual-API coexistence pattern made finance comfortable enough to sign off on the cutover. Production concurrency controls handle the nightly reconciliation, and the runbook calls out the rate-limit ceiling so on-call is not surprised. Architecture diagram is in our internal wiki, not a slide deck.

    • Operator note

      We kept the exception queue and the sign-off authority on anything over $5K, which is the part our auditors actually care about. Up to 90% reduction in manual data entry touchpoints on the long-tail invoices. The Loom walkthrough they ship with the handoff is what made adoption easy for the AP team. Handwritten correction fields on scanned PDFs still go to the queue, and the system flags them rather than guessing, which is exactly what we wanted.

    • Operator note

      Up to a 12-minute mean time from alert to first triage hypothesis across 14 sites, down from a multi-hour on-call escalation. The agent does not act on hardware faults, it pages a human, which is the right line. The MCP server exposing UniFi telemetry as typed tools is the part we are now extending ourselves, with the patterns documented in the standards doc they left behind.

    • Operator note

      Catches up to 30% week-over-week cost drift inside 24 hours of the spend posting. Previously we reviewed cost monthly and discovered drift in arrears. FinOps owns the ticket queue and the agent never closes its own work, which is the boundary we wanted. The daily Slack digest is short enough that the team actually reads it instead of muting the channel.

    • Operator note

      LLM data-mapping agents collapsed a 12-week MLS integration into a 3-day deployment sprint. Low-confidence field mappings are routed to a human data engineer with the source samples attached, which made our data team comfortable adopting the workflow. The weekly regression eval against the source schema has already caught two upstream drift events that would have shown up as silent corruption a month later under our old process.

    • Lovable

      Recognition

      Lovable Champion and community leader with 10,183 verified edits across 277 active days. The Champion designation is awarded by the Lovable team based on shipping volume, consistency, and community contribution inside the platform. The edit count and active-day count are pulled from the platform's verified telemetry, not self-reported.

    • Anthropic Academy

      Recognition

      Completed 9 Anthropic Academy courses including Agent Engineering, Claude Code, MCP, and Context Engineering. Coursework covers the same agent patterns we ship inside Workflow Rescue and Fractional FDE engagements, including failure-mode taxonomy and eval methodology.

    • Favikon

      Recognition

      Top 5 AI Education ranking, Favikon, November 2025. Ranking based on LinkedIn audience reach and engagement on AI-education content. 57K LinkedIn followers as of the same period. The ranking methodology is published by Favikon and is independent of any TechTide AI input.

    • FigGlow.ai

      Recognition

      Co-founder of FigGlow.ai with Shane Spencer. Carousel SaaS for LinkedIn-native publishers. The product engineering informs our practice around small, focused agents that ship a single workflow well rather than agentic-everything platforms that ship nothing in production.

    • Multi-provider operations

      Recognition

      2.27 billion OpenAI tokens, 559 Codex sessions, 30+ Claude Code skills, two production MCP servers, single implementations utilizing production concurrency controls. Numbers reflect production usage across our own engagements and tooling, pulled from provider dashboards, not estimated. We operate multi-provider by default; vendor lock-in is a named failure mode we design against.

    [ CASE FILES INDEX ]

    Every case file, on one page.

    Mid-market SaaS (sanitized)

    2026-Q1

    Stripe billing reconciliation, autonomous worker mesh

    Production concurrency controls

    Regional services firm (sanitized)

    2025-Q4

    Invoice intake, manual data entry reduction

    Up to 90% reduction in manual data entry touchpoints

    US enterprise IT (sanitized)

    2025-Q3

    Intune policy rollout assistant

    JWT/RLS scaffolding deployed in 3 days

    Mid-market hospitality (sanitized)

    2025-Q3

    UniFi multi-site network triage agent

    12-minute mean time to first triage

    Mid-market platform team (sanitized)

    2025-Q2

    Azure cost guardrails and anomaly review

    Up to 30% week-over-week cost drift caught early

    [ 13-YEAR OPERATOR LEDGER ]

    Before AI, I was already shipping.

    2013, 2015

    Wendy's (Help Desk)

    Tier-1 / Tier-2 Support

    Per Scholas CompTIA A+/Network+ (2013). First production on-call rotation.
    2015, 2018

    OhioHealth

    IT Operations

    HIPAA-scoped change windows. Zero patient-impacting outages attributable to assigned changes.
    2018, 2021

    Sedgwick

    IT Operations Engineer

    Standardized endpoint baseline across multiple regional offices.
    2021, 2024

    Blair IT

    Senior Systems Engineer

    Owned multi-tenant Azure, Intune, and UniFi rollouts. Customer renewals on assigned book.
    Oct 2024

    TechTide AI (founded)

    Founder & CTO

    13 years of mixed IT across support, systems, cloud, architecture, and engineering pointed at the AI implementation gap.
    Read the full ledger

    [ ALEX ON STAGE ]

    Keynotes, workshops, panels.

    Alex speaks on operator-grade AI implementation: Claude Code rollouts inside existing engineering orgs, MCP server hardening, the failure modes that kill 50% of pilots at the org layer, and the anti-hype rules that keep production systems honest. Audiences are CTOs, AI task-force owners, and engineering leaders, not generalist business crowds.

    Past and upcoming engagements are maintained on alexcinovoj.com so the calendar cannot drift stale here. Booking, fees, and format options live on the same page.

    Book Alex to speak

    [ FAQ ]

    The questions buyers actually ask.

    Pricing, scope, refusal criteria, eval methodology. Answered in writing so we do not repeat them on every call.

    • How much do your engagements cost?

      Three tiers, all fixed-fee. Production Triage is $5,000 for a 7-day architecture review and go/no-go call on a stuck Claude pilot. Workflow Rescue is $25,000 to $40,000 for a 21-day fixed-scope production deployment of one stuck workflow. Fractional FDE is $25,000 to $40,000 per month with a 3-month minimum, structured as an embedded Forward Deployed Engineer model. We do not bill hourly, we do not run open-ended retainers, and we do not negotiate scope in arrears. Each engagement has a written scope and a written outcome up front.

    • What is a Production Triage and why does it cost $5K?

      Seven days, $5,000, one written deliverable: an architecture review of your existing Claude pilot, a sequenced 21-day fix list, and a go/no-go call on whether the pilot is worth shipping. We read the code, the prompts, the logs, the MCP wiring, and the eval suite (or note its absence). The price is the qualification gate. It filters out projects that need a Workflow Rescue from projects that need a different vendor or a different decision, and it gives both sides written evidence to commit to or walk away from.

    • Who is your ideal client?

      An engineering leader, CTO, or AI task-force owner whose Claude pilot is stuck between demo-good and production-ready. Three weeks from a deadline, or six months past one. Existing in-house engineering capability that can own the system after handoff. US-based for billing and timezone alignment, primarily mid-market SaaS, IT-heavy orgs, fintech, and operations-heavy verticals. We are not a fit for greenfield prototypes that have not been built yet (that is your team's job) or for clients looking for automation-consultancy strategy decks.

    • What counts as a blocked pilot?

      A Claude or agentic pilot that demos cleanly but cannot move to production. Common shapes: MCP integrations are leaking permissions or burning tokens; the eval suite does not exist or has not been run on real traffic; observability is absent so on-call cannot triage; the architecture cannot scale past the demo entity count; the team built it once and cannot extend it without the original contractor. We have a written triage checklist; if your pilot matches three or more lines on it, Production Triage is the right next step.

    • When will you refuse a project?

      When the pilot has no salvageable architecture. When the ICP is wrong (consumer, low-trust, or no in-house engineering team to own the handoff). When the timeline is shorter than the fixed scope and there is no path to extend it. When the budget cannot cover the named outcome and the conversation is about discounting rather than narrowing scope. We say no out loud and we say it in writing. Refusal is part of the offer. We rescue the half worth saving and refuse the rest.

    • What is in scope for a Workflow Rescue?

      Fixed-scope 21-day production deployment of one stuck workflow. In scope: prompts, retrieval, tools, guardrails, hardened MCP integrations with scoped auth and rate limits and audit logs and output validation, regression eval suite on real traffic, observability wired to your existing stack, runbook, pair-programming handoff to the owning engineer, architecture doc, infrastructure-as-code, every secret in your vault. Out of scope: a second workflow (that is a second Rescue), long-tail maintenance (that is Fractional FDE), org-design or change-management consulting.

    • What does completing Anthropic Academy coursework actually mean?

      Completed 9 Anthropic Academy courses to date including Agent Engineering, Claude Code, MCP, and Context Engineering. Each completion is a coursework certificate with a written or applied component reviewed by Anthropic. The coursework covers the same agent patterns and failure-mode taxonomy we ship inside Workflow Rescue and Fractional FDE engagements. Coursework is necessary, not sufficient. It gets you in the door; the case files are what close the door behind you.

    • Are you Columbus-only?

      Headquartered in Columbus, Ohio. Engagements are US-based for billing and timezone alignment. Workflow Rescue and Fractional FDE engagements are run remote-first with optional onsite weeks negotiated case by case. Production Triage is fully remote. Local Columbus and central Ohio clients are welcome; we are not exclusive to the region. Our 13 years of mixed IT across support, systems, cloud, architecture, and engineering is part of why we are based here.

    • How do you build production MCP servers?

      Two production MCP servers shipped to date. Patterns: scoped OAuth, typed tools, rate limiting, audit logging, output validation on every response. We default to read-mostly scopes with explicit write-confirmation gates. Failure mode named: MCP transport latency under high concurrency is the dominant tail-latency contributor, mitigated by tool-level timeouts and a circuit breaker. Handoff package: deployment runbook, eval suite, written threat model. The same hardening practice ships inside every Workflow Rescue and informs the standards doc left behind by every Fractional FDE engagement.

    • What is your eval methodology?

      Regression evals on real traffic before launch, sampled cadence after launch. The suite covers the happy path, the named failure modes, and adversarial cases pulled from your incident history. We do not ship vibes; we ship the eval report. Failure mode named: eval drift when the underlying model version changes, mitigated by pinning the production model and gating upgrades through a re-run of the full suite. Up to 90% pre-launch confidence on the bounded scope. Out-of-scope inputs are routed to the exception queue, never auto-handled.

    • Why Fractional FDE instead of a fixed Rescue?

      Workflow Rescue gives you one workflow in production in 21 days. Fractional FDE gives you ongoing senior AI implementation muscle across three months: pair programming, design reviews, MCP and Claude Code training, two to three additional production workflows shipped alongside your engineers, written standards docs, hiring-loop support. You leave with senior in-house capability, not dependency. Best fit after one or two successful Rescues, or when the team needs to build agentic muscle internally rather than buy a single workflow. Each month has a written work plan to prevent scope creep.

    • What providers and tools do you operate?

      Multi-provider by default. 2.27 billion OpenAI tokens and 559 Codex sessions in production. 30+ Claude Code skills shipped. Two production MCP servers. Single implementations utilizing production concurrency controls when the workload supports it. Stack defaults: Anthropic, Claude Code, MCP, Lovable, Supabase, n8n, Python, TypeScript, React, Tailwind, Vite. Vendor lock-in is a named failure mode we design against; orchestration layers are written to be portable across providers.

    • Do you speak at events?

      Yes. Keynotes, workshops, panels. Book through alexcinovoj.com.

    [ ANTI-HYPE MANIFESTO ]

    Logs over vibes. Production over theater.

    No "optimal", no "always", no "average X". Every velocity claim names its failure mode in the same paragraph. Every case file links to an architecture diagram, a Loom, or an arXiv reference. The voice is the product.

    Read the manifesto

    [ THE OPERATOR ]

    Alex Cinovoj. Columbus, OH.

    13 years of mixed IT across support, systems, cloud, architecture, and engineering, with the last 2 focused on AI implementation. Lovable Champion and community leader with 10,183 verified edits across 277 active days. Completed 9 Anthropic Academy courses (Agent Engineering, Claude Code, MCP, Context Engineering). Co-founder FigGlow.ai (with Shane Spencer). 57K LinkedIn followers. Top 5 AI Education, Favikon, November 2025.

    The full story

    Start with the audit. See what the layer would answer first.

    $1,000. One week. A written map of your tools, your highest-leverage workflow question, and the scoped first build path to answer it.

    Book the Workflow Intelligence Audit — $1,000