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service 06 · ai business tools

AI that does the work.
Not demos
that gather dust.

> Practical AI baked into the systems your team already uses. Workflow automations, custom GPTs, document AI, agents, internal copilots — scoped to one job, shipped in weeks, measured in hours saved.

SHIP IT
OPS · RUNNING
internal AI tools → in production
HOURS SAVED · 200/MO
Avg time back per business unit
on workflow + document automations
SHIP · 4 WEEKS
From audit to first tool live
starts producing value before month-end
ROI · 5–10x
Year-one return vs. retainer
on tools your team actually uses
// SECTION 02 — WHY IT MATTERS

most AI projects die in pilot

Buying ChatGPT seats isn't a strategy. The wins come from boring, well-scoped tools wired into the workflows your team runs every day — not another playground tab.
88%
of corporate AI pilots never hit production
40%
of knowledge work is automatable today
5–10x
ROI on tools that ship vs. shelfware

AI is not
the strategy.

AI Business Tools are scoped solutions to problems your team already has — the report nobody wants to write, the inbox triage, the proposal drafting, the spec extraction, the customer support tier-1. We pick the highest-leverage one and ship it in weeks.

No multi-quarter "AI transformation" decks. No copy-paste GPT wrappers. No vendor that vanishes after handoff and leaves you with a Replit project nobody can debug. Built on the stack your team already runs — Slack, Notion, HubSpot, Google Workspace, Jira, your data warehouse — not a parallel universe.

Audit. Pick the win. Ship it. Train the team. Iterate. Repeat with the next one.

// SECTION 03 — WHAT WE DO

the five lanes

Strategy · Workflow · Copilots · Document AI · Ops. Pick a lane below.

AI Strategy + Audit

Before you buy a single license. Where AI fits in your business, where it doesn't, and which one tool would save the most hours fastest. Tight scope, ranked by ROI.

  • Workflow + tooling audit
  • Time-spent + repetitive-task mapping
  • Use-case ranking by ROI / risk / effort
  • Stack + vendor recommendations
  • Build vs. buy decisions
  • Data + privacy readiness review
  • 12-month roadmap + investment plan

Typical lift

The audit alone pays for itself — most teams have 3–5 obvious automation wins they've been ignoring while chasing a chatbot.

2wk
audit phase
3–5
scoped wins identified

Workflow Automation

The boring, high-ROI work. Connect the tools you use, drop AI in the parts that need judgement, kill the manual copy-paste. Make / n8n / Zapier with LLMs in the middle.

  • Make.com / n8n / Zapier builds
  • LLM steps for classification + extraction
  • CRM ↔ inbox ↔ docs sync
  • Slack + Teams notification triggers
  • Approval + human-in-the-loop steps
  • Error handling + retry logic
  • Run-cost monitoring + budgets

Typical lift

One well-built workflow saves a person 5–10 hours a week. Five workflows saves a head count.

5–10h
saved per workflow / wk
2–3wk
build to ship

Custom GPTs + Agents

Internal copilots that know your business — your tone, your data, your guardrails. Built on OpenAI / Anthropic / Azure with proper retrieval, eval and access control.

  • Custom GPT + Claude Project builds
  • RAG over your docs + databases
  • Agent orchestration (LangGraph / DSPy)
  • Tool-use + function calling
  • Eval harnesses + regression suites
  • Prompt versioning + A/B testing
  • Role + permission scoping

Typical lift

A well-scoped internal copilot replaces 30% of a knowledge worker's research + drafting time. Not magic — just leverage.

30%
drafting time reclaimed
100%
audit logs + evals

Document + Knowledge AI

Drowning in PDFs, contracts, specs, transcripts. We turn document piles into searchable, queryable knowledge — with citations, so nobody trusts a hallucination.

  • Knowledge base + wiki indexing
  • Contract + spec extraction pipelines
  • Meeting + call transcript summarisation
  • Citation-first answer UX
  • Vector DB setup (Pinecone / pgvector / Qdrant)
  • Hybrid search (vector + keyword)
  • Permissioned search across SaaS apps

Typical lift

If your team Slacks the same five questions every week, that's a knowledge tool waiting to happen.

10x
faster info retrieval
100%
cited answers

Integration + Ops

The unsexy part that determines whether AI tools survive past launch. APIs, monitoring, governance, eval, cost control, hand-off to your team. Production-grade, not vibes.

  • API + webhook plumbing
  • LLM gateway + cost monitoring
  • Eval + observability (Langfuse / Helicone)
  • PII redaction + data loss prevention
  • SOC 2 / GDPR-aligned data flows
  • Internal docs + Loom walkthroughs
  • Quarterly review + iteration retainer

Typical lift

Most internal AI tools die because nobody owns ops. We do, until your team is ready to take the keys.

99.5%
uptime SLA
monthly
cost + eval review
// SECTION 04 — HOW WE RUN IT

the six-step motion

Audit, scope, build, deploy, train, iterate. Every tool measured. Every tool maintainable.
01

Audit

Workflow + tooling review. Where the time goes, where the leverage is. Ranked list of opportunities.

week 1–2
02

Scope

Pick the highest-ROI win. Define inputs, outputs, success metric, edge cases. Signed off before build.

week 2
03

Build

Workflow, agent, or tool built on your stack. Eval harness, guardrails, logging baked in from day one.

week 2–4
04

Deploy

Roll out behind a feature flag to a pilot user group. Watch logs. Fix the thing that breaks first — always something.

week 4–5
05

Train

Loom walkthroughs, internal docs, and a live session with the team. They own it before we leave.

week 5–6
06

Iterate

Monthly evals, cost review, prompt + retrieval tuning. Pick the next tool. Repeat.

month 2+
// SECTION 05 — INVESTMENT

priced per scope

Every build is different — data sensitivity, complexity, integrations, ongoing eval needs. We quote per scope, not per seat. Send a brief — 48h turnaround on a shaped number.
Quote on request
// AI BUSINESS TOOLS

Project + retainer.

Fixed-price build for the first tool. Optional monthly retainer for ops, eval and the next tool.

Pricing depends on scope — number of integrations, data volume, eval requirements, whether RAG is involved, and how regulated the data is. We shape a fixed price once we understand what "done" looks like.

// EVERY ENGAGEMENT INCLUDES
  • Audit + use-case ranking
  • Scoped build (workflow / agent / tool)
  • Eval harness + observability
  • Guardrails + cost monitoring
  • Loom walkthroughs + internal docs
  • Team training session
  • 30-day post-launch support
// WHAT MOVES THE NUMBER
  • Number of integrations
  • Data sensitivity (PII / regulated)
  • RAG + vector DB scope
  • Custom UI vs. existing tool
  • Eval + regression coverage
  • Multi-tenant / multi-team
  • Ongoing ops retainer in/out
Request a quote
"BT shipped a contract-extraction tool that saved our ops team 25 hours a week — we'd been trying to build it internally for nine months."
Allied Automation · chief operating officer
// SECTION 07 — FAQ

questions we get

How fast can we ship a tool?+

Audit takes 1–2 weeks. The first scoped tool typically lands in production 2–4 weeks after sign-off — so you're seeing real value inside month one. Anyone promising a custom AI agent in two days is shipping a demo, not a tool.

Why no fixed pricing?+

Because builds vary wildly. A scoped Slack workflow with three integrations is a different beast to a RAG copilot over 50k contracts with role-based access. Pre-baked tiers either under-deliver or over-charge. We scope then quote.

What model providers do you use?+

Whatever fits. Anthropic Claude, OpenAI GPT, Google Gemini, open-source via Bedrock or Together. We pick per use case based on cost, latency, and quality — and route through a gateway so you can swap without a rewrite.

What about our data security?+

Enterprise-tier API agreements (no training on your data). PII redaction at the gateway. Role-based access on retrieval. SOC 2 / GDPR-aligned data flows. We won't ship anything we wouldn't run on our own data.

Do you build chatbots?+

Sometimes — if a chat UX is genuinely the right interface. Often it isn't. A button in HubSpot, a Slack slash-command, or a scheduled job that drops a Notion page is usually higher leverage than another chat window.

What stack do you build on?+

Whatever you already run. Make.com / n8n / Zapier for workflows. LangGraph / DSPy for agents. Pinecone / pgvector / Qdrant for retrieval. Langfuse / Helicone for evals. Slack, Notion, HubSpot, Google Workspace, Salesforce — all fair game.

Do we own the code?+

Yes. Source in your GitHub. Infra in your cloud accounts. Prompts and eval suites versioned in your repos. The retainer is for ops + iteration — you're never locked in to keep us around.

What if it doesn't work?+

Every tool ships with a success metric defined in the scope. If it doesn't hit — we iterate on us, not on you. Fixed-price means fixed-price.

// REQUEST A QUOTE

tell us where AI fits.

Drop a brief. We'll come back inside 48h with a shape, a price, and a start date — or questions if we need more to scope the build properly.

Fixed-price scope
Use-case + ROI ranking
Realistic timeline forecast
48-hour turnaround
No obligation, no pitch deck
Intro call if useful