AI consulting · Implementation · Training

Audit it. Build it. Teach it. Your AI partner, end to end.

Yan Soft Labs is the AI consulting, implementation and training partner for growing companies and enterprise teams. We audit your operations, shape your AI strategy, build agentic AI and automation workflows — and train your people to run them.

  • Consulting before any build
  • Human-in-the-loop by design
  • Vendor-neutral · no lock-in
Example agentic workflow
  1. 01 · Business triggerForm submitted: “Need help automating our onboarding”
  2. 02 · AI agentSales intake agent
  3. 03 · ReasoningReads the request, checks company fit and urgency
  4. 04 · Business toolsCRM · Company data · Calendar
  5. 05 · Automated actionCreates lead, drafts a tailored reply with meeting slots
  6. 06 · OutcomeLead answered while interest is high
Example workflow: Business trigger: Form submitted: “Need help automating our onboarding”. AI agent: Sales intake agent. Reasoning: Reads the request, checks company fit and urgency. Business tools: CRM · Company data · Calendar. Automated action: Creates lead, drafts a tailored reply with meeting slots. Outcome: Lead answered while interest is high

Vendor-neutral across the platforms you already run — technologies, not client logos

OpenAI, Anthropic Claude, Google Gemini, Mistral, Open-weight models, HubSpot, Salesforce, Pipedrive, Zoho CRM, Zendesk, Intercom, Freshdesk, Gorgias, Google Workspace, Microsoft 365, Slack, Microsoft Teams, Notion, QuickBooks, Xero, NetSuite, Stripe, Shopify, WooCommerce, BigCommerce, n8n, Make, Zapier, Power Automate, PostgreSQL, BigQuery, Snowflake, AWS, Azure, Google Cloud

One partner, three disciplines

Advise. Implement. Enable.

Most AI programs stall in the hand-offs — between the strategy firm, the vendor and the people expected to use the result. We cover all three, so nothing gets lost.

Know where AI pays off — before you invest.

We audit processes, data, systems and skills, then turn the evidence into an AI strategy, governance model and roadmap your leadership can back.

  • Independent AI audit & readiness assessment
  • Audit of AI systems you already run
  • Use-case portfolio, ROI and operating model
  • Responsible-AI policy and governance

The problem

AI ambition is high. Real results are rare.

The technology is ready. What’s usually missing is clarity on where to start, systems that work in production, and people equipped to use them.

01

No clear starting point

Dozens of ideas, no evidence on which will pay off — so nothing gets prioritized.

What it costs youBudget spent on the wrong pilots

02

Pilots that never ship

Impressive demos that lack integration, security, testing and an owner.

What it costs youStalled momentum and sceptical leadership

03

Busywork between systems

Copy-paste, inbox triage and spreadsheet reporting eat skilled people’s week.

What it costs youSlow responses and costly errors

04

Teams without AI skills

Licenses bought, adoption low, and unsafe use of public tools.

What it costs youWasted spend and data risk

How we engage

Consulting first. Then we build what’s justified.

We never automate a process we haven’t understood. Every engagement starts with a conversation and an audit, so what we implement — and what we train — is grounded in evidence.

Start with a strategy call (opens Calendly in a new tab)
  1. Step 1 · 30 minutes

    Consultation

    A strategy call to understand your goals, constraints and where AI might help. No sales script, no build talk yet.

  2. Step 2 · typically 1–3 weeks

    AI audit

    We map processes, data, systems and skills, and score every opportunity by value, effort and risk.

    About the AI audit
  3. Step 3

    Strategy & roadmap

    Priorities, governance, architecture and success measures agreed in writing — you decide what gets built.

  4. Step 4 · weekly demos

    Implementation

    Agentic AI, automations and integrations built in focused sprints, tested on your real examples.

  5. Step 5

    Training & adoption

    Leaders, teams and builders trained to use, supervise and improve what was built.

    About AI training
  6. Step 6 · ongoing

    Optimize & scale

    Measure against the baseline, improve, and expand to the next priority on the roadmap.

Agentic AI in practice

Specialist agents we design, build and train your team to run

Not one “do-everything” bot — focused agents with narrow permissions and a named human checkpoint, customized to your workflow after the audit.

Intake Agent

Sales & client intake

Reads every inbound inquiry, qualifies it against your criteria, enriches the record and books the right next step.

  • CRM
  • Email
  • Calendar

Rep approves replies to new accounts

Triage Agent

Customer support

Classifies tickets, pulls order and account context, resolves routine requests and prepares the rest for your team.

  • Helpdesk
  • Order data
  • Knowledge base

Refunds above a threshold need approval

Document Agent

Finance & operations

Extracts and validates data from invoices, applications and forms, then files it in the right system.

  • Inbox
  • Accounting / ERP
  • Storage

Low-confidence fields go to review

Research Agent

Sales & strategy

Builds account briefs and market summaries from approved sources, with citations for every claim.

  • Web sources
  • CRM
  • Docs

Analyst reviews before sharing

Reporting Agent

Leadership & ops

Compiles recurring reports from live data and writes the commentary your managers used to write by hand.

  • Data warehouse
  • Sheets
  • Slack

Owner signs off monthly packs

Knowledge Agent

Whole company

Answers staff questions from your policies and procedures, and shows where each answer came from.

  • SharePoint / Drive
  • Wiki
  • Teams / Slack

Respects document permissions

How we deliver agentic AI

Free self-assessment

How AI-ready is your organization?

Six quick questions. You’ll get a readiness profile across strategy, processes, data, systems, skills and governance — and the engagement we’d recommend as your first step.

  • Takes about a minute
  • Runs in your browser — nothing is sent
  • Discuss your result on a free strategy call
Question 1 of 6 · StrategyDoes leadership have clear AI priorities?

Runs in your browser. Nothing is sent or stored.

Before vs after

What changes when AI is implemented properly

AI strategy

Before: Scattered pilots and opinions; no agreed priorities or policy.

After: An evidence-based roadmap, governance and owners for every initiative.

Inbound leads

Before: Read when someone has time; details copied into the CRM by hand.

After: Qualified, enriched and answered by an agent; reps approve and focus on conversations.

Documents & reporting

Before: Details re-typed from PDFs; Friday afternoons lost to spreadsheets.

After: Fields extracted and matched; reports compiled with a first-draft commentary.

Team capability

Before: Licenses unused; staff unsure what’s safe.

After: Confident, trained teams and internal champions who build their own workflows.

How agentic AI works

Signals in. Decisions made. Work done.

A business event arrives, an AI agent interprets it within your rules, your tools are updated, and one clear outcome is delivered — with a person in the loop wherever it matters.

  1. Signals from email, forms, tickets and systems
  2. Agent core reasons with your rules and data
  3. Tools updated through secure integrations
  4. Outcome delivered, logged and measurable

Integration ecosystem

Connected to the tools you already run

No rip-and-replace. Agents and automations read from and act in your existing CRM, helpdesk, finance, documents and data — through secure, least-privilege integrations.

Signals from email, CRM, documents and helpdesk flow into a governed AI agent core, which produces actions, approvals and reportsEmail & formsCRMDocumentsHelpdeskActions in your toolsApprovalsReports & alertsGoverned AI agent core

See integrations

Business outcomes

What every engagement is designed to deliver

We agree the measures with you before we build or train — and capture a baseline so results can be compared honestly.

Confident AI decisions

Investment directed by evidence, not hype — with governance leadership trusts.

Less repetitive work

Hours of copy-paste, sorting and re-typing handled by agents and automation.

Faster response times

Leads, customers and colleagues answered while it still matters.

Scalable operations

More volume handled without adding the same amount of admin.

Adoption that sticks

Trained teams and champions who use and improve AI every day.

Safer AI use

Clear policy, human checkpoints and audit trails across every system.

1–3 weeks
Typical AI audit
3 disciplines
Advise · Implement · Enable
8 services
One accountable team
24/7
Automations work around the clock

Why Yan Soft Labs

Strategy, engineering and training — without the hand-offs

How our model compares with the usual ways companies source AI help.

CapabilityYan Soft LabsStrategy-only consultancyTool vendor / platformFreelance builder
Independent AI audit & strategyYesYesNoPartial
Builds production agentic AI & automationYesPartialPartialYes
Trains your teams to own itYesPartialPartialNo
Vendor-neutral recommendationsYesYesNoPartial
Governance & human-in-the-loop by designYesPartialPartialNo
You own the code and documentationYesn/aNoPartial

FAQ

Frequently asked questions

Do you work with small or large businesses?

Both. We work with growth-focused SMBs, mid-market firms and enterprise teams. The audit scales to the size of your organization.

Do you only build AI systems?

No. We start with an audit and a strategy to make sure AI is applied where it actually makes sense. Sometimes the right answer is a simple workflow automation — or a process change with no AI at all.

Is AI a replacement for our team?

No. We design AI to augment people — taking on repetitive work so your team can focus on customers, judgment and higher-value tasks.

How long does an AI audit take?

Typically one to three weeks, depending on the number of teams, processes and systems involved.

What is the difference between AI agents and workflow automation?

Workflow automation follows fixed rules to move data between systems. AI agents can interpret unstructured inputs and decide the next step within the limits you set. Most production systems combine both.

Which tools and AI models do you work with?

We are tool- and model-agnostic: leading LLM providers such as OpenAI, Anthropic and Google, automation platforms such as n8n, Make and Zapier, and custom code when needed — connected to your existing CRM, helpdesk, ERP and data.

How do you handle data security and privacy?

We follow least-privilege access, minimize the data AI models see, choose provider configurations that do not train on your data where available, log every automated action, and document where data is processed.

Do you offer AI training for our teams?

Yes. We run executive AI briefings, role-based generative AI workshops for every team, and hands-on agentic AI and automation labs for builders — customized to your tools, processes and policies.

Do you build during the first conversation?

No. Every implementation starts with consulting: we understand your goals, audit the relevant processes and agree scope and success measures before anything is built.

Who owns what you build?

You do. We hand over code, configuration and documentation, and train your team so you are not dependent on us.

Let’s find where AI will pay off for you

Book a free 30-minute strategy call. We’ll discuss your goals, tell you honestly where AI fits — and where it doesn’t — and outline the right first step: an audit, a training program or an implementation.

  • 30 minutes, no obligation
  • Honest fit assessment
  • Clear next step
Book a call (opens Calendly in a new tab)AI audit