Services / flagship / Build engagement

AI Agent Development

A custom AI agent trained on your business — running 24/7, measurable, and yours.Your business has processes. Quotes, scheduling, customer follow-up, vendor coordination, expense categorization, document review. We build an AI agent that handles them — trained on your SOPs, wired to your tools, with a dashboard you can actually read. Cloud-hosted by default. Eval harness included so you know it works. Human-in-the-loop guardrails on every action that touches money or customers.

Book a Discovery Call Request custom scope services index

price

from $2,600

timeline

4 weeks

cadence

one-time

scope

One-time / fixed scope

LangGraphOpenAI / AnthropicTool callingEval harnessObservabilityCloud-hostedBYOK

// compare the flagship suite

Compare flagship offers

Five engagements. Pick what matches your situation.

See all services

Engagement	Price	Timeline	Mode	Best for	Action
AI Implementation Consulting	from $1,000	2 weeks	Audit	Don’t know where AI fits	View
AI Agent DevelopmentYou’re here	from $2,600	4 weeks	Build	Repetitive ops work eating your week	—
AI Voice Agent	from $1,800	3 weeks	Build	Missed inbound calls	View
AI Lead Engine	from $2,200	4 weeks	Build	Targeted outreach without spam	View
Agent Operations Retainer	from $600/mo	Monthly	Operate	Already shipped — keep it sharp	View

01// why this exists

A trained agent that knows your business — working 24/7 with humans in the loop.

We build AI agents the way real software gets built: scoped to one job, trained on your SOPs, wired to the tools you already use, with an eval harness that proves it works. Cloud-hosted by default. Hard monthly spend cap. Approval queue for anything that touches money or customers. You get a dashboard you can actually read — and an agent that gets better, not flakier.

BYOK

Pay LLM providers direct — no markup on tokens

Eval harness

Regressions caught in CI before they reach production

Spend cap

Hard ceiling you set — no surprise OpenAI invoices

Human-in-loop

Approval queue on every action that touches money or customers

02// how it works

The architecture, end to end.

No black boxes. Here's the actual shape of the system you get — with the guardrails, eval loops, and human approvals where they belong.

AI Agent architecture

Signal in → grounded reasoning → tool use → human-approved action.

inputcoretooloutputguard

// where this fits

Real use cases we ship.

01
Quote & proposal generation
Inbound request → trained on your pricing → drafts quote → you approve → sends.
02
Customer follow-up
Day-3, day-7, day-30 nurture sequences personalized to each conversation.
03
Invoice + expense categorization
Auto-codes and posts to QuickBooks/Xero. Flags anything weird for human review.
04
Scheduling & coordination
Calendar-aware booking, rescheduling, and confirmation across your team and clients.
05
Document review & extraction
Contracts, intake forms, vendor docs — pulls fields, flags risk, files cleanly.
06
Internal Q&A on your SOPs
Slack / Teams bot trained on your playbooks. Cites source. Says "I don’t know" honestly.

04// what you walk away with

The outcome, not just the output.

01A custom agent trained on YOUR business processes — not a generic assistant
02Live dashboard showing every action, cost, and decision the agent makes
03Eval harness that catches regressions before they hit production
04Human-in-the-loop guardrails on financial + customer-facing actions
05Monthly cost cap so you never get a surprise OpenAI bill
06Documented playbook so your team can update prompts and tools without us

// agent flow

How the agent thinks.

The decision graph behind the engagement. Inputs, branches, and the point where a human stays in the loop.

// your command center

The dashboard you actually use.

Every flagship engagement ships with a control panel — live activity, eval pass rate, spend cap, and an approval queue you can act on from your phone.

Live · Production

Sage Agent — Operations

Real layout from a production deployment (anonymized).

agent.v1.4

Tasks handled / 24h

847

+12% vs last week

Avg resolution

38s

−6s

Hands-off rate

91%

+3pp

Hours saved / mo

127

≈ $4.8k labor

Live activity

last 5 min

12sQuote drafted for ACME Corp — $4,250 — sent to approval queue
48sCustomer follow-up sent: 6 leads · day-3 nurture
2mVendor invoice categorized & posted to QuickBooks (auto)
4mRefund $312 — over $250 threshold — awaiting human review
6mScheduling: rescheduled 2 appointments after weather alert
8mEval run: 42/44 passed (2 edge cases flagged for review)

Eval pass rate95%

42 / 44 test cases passed · last run 12m ago

Monthly spend$182 / $500

Auto-pause at cap. Slack alert at 80%.

Awaiting approval3

Refund request > $250 — review
Outbound email batch — 12 ready
1 more queued

// cost forecast

Estimate your monthly run cost.

Cost estimator

Forecast your monthly run cost

Drag the slider. Real cost is capped in production — you set the ceiling.

Volume5,000 tasks / mo

50025,000

Base infra

$95 / mo

Hosting · observability · evals

Variable (LLM + tools)

$200 / mo

≈ $0.04 per tasks

Total monthly

$295 / mo

Forecast — actual capped in prod

Recommended monthly cap: $450 — we set this hard ceiling in production. Agent auto-pauses when hit, with a Slack alert at 80%. You raise it only if you want to.

80% alert

Estimate uses average token costs and observed agent behavior in similar deployments. Final budget is set with you during scoping and enforced with a hard monthly cap. BYOK supported — pay your provider directly, we don't mark up tokens.

05// methodology

How the engagement actually runs.

Concrete phases, concrete artifacts. You always know where we are and what comes next.

Week 1
Discovery + agent design
Process mapping with your team. Identify the workflows the agent will own. Design the tool library, knowledge base structure, and eval criteria. Lock the scope.
Process mapTool specEval rubricCost forecast
Week 2
Build — runtime + tools
Stand up the agent runtime, wire the tool library to your stack, ingest your SOPs into the knowledge base. First end-to-end run on test data.
Agent runtime deployedTool libraryKnowledge baseFirst eval run
Week 3
Evals + dashboard
Build out the eval harness with real cases from your business. Stand up the operations dashboard. Wire human-in-the-loop approval flows on high-risk actions.
Eval harnessOps dashboardApproval flowsCost monitoring
Week 4
Pilot + handoff
Soft-launch with one team, monitor evals and dashboard, tune prompts. Documented playbook + 60-minute training session + 30 days Slack support.
Operations playbookTraining sessionSlack channelTuning report

// track record

Receipts, not promises.

4 weeks: Median delivery · spec to launch
30–80: Eval cases at launch · real-workflow grounded
$50–$400: Typical run cost / mo · small business volume

06// scope

Concrete artifacts you keep — and what we leave out.

Working code, written docs, dashboards your team owns. We also list what this engagement deliberately does not cover, so scope is honest before you sign.

// deliverables

Agent runtime (LangGraph or equivalent) deployed to your cloud or ours
Tool/function library wired to your stack — CRM, calendar, billing, docs, email
Knowledge base built from your SOPs, processes, and reference docs
Eval harness with 30–80 test cases derived from your real workflows
Operations dashboard — live activity, cost meter, eval scores, error log
Human-in-the-loop approval flows for high-stakes actions
Monthly cost cap + alerting
Operations playbook (how to add tools, update prompts, review evals)
30 days post-launch Slack support + tuning

// not included

Ongoing agent operations (use Agent Operations Retainer)
Building net-new business processes (we automate what exists)
Replacing licensed software (we wire to existing tools)
On-premise installs (cloud-hosted by default; VPC available as enterprise add-on)

// add-ons

Extend the engagement.

Additional tool integration

+$480

Wire the agent to one additional system beyond the base scope (e.g., a niche CRM, ERP, or industry-specific tool).

Custom dashboard branding

+$600

White-label the operations dashboard with your branding, custom domain, and SSO.

VPC / on-premise deployment

+$2,000

Deploy the agent inside your private cloud or on-premise environment for compliance-sensitive workloads.

Multi-agent orchestration

+$1,400

Add a second specialized agent that hands off to the first (e.g., research agent + execution agent).

Sample deliverables

See the artifact, not the marketing.

Real shape, redacted content. Pick a tab to preview what ships.

Sample Audit Report

Twelve-page audit excerpt: scope, methodology, findings ranked by impact, and a prioritized fix list. Redacted.

Request after intro call

Sample provided after intro call · ask sage@sageideas.dev

How we reduce risk

Money-back if you're not happy in week 1

Reset the engagement before momentum builds. No invoices to dispute, no awkward email.

Async-first, weekly demos, no surprises

You see exactly what shipped each week. No status meetings to attend, no reports to chase.

Code is yours from day 1 — no lock-in

Your repo, your infra, your accounts. We work in your stack. You can take the work in-house at any time.

07// questions

Honest answers.

01How is this different from buying ChatGPT Enterprise?

ChatGPT is a general assistant. This is a specialist trained on your processes, wired to your tools, with measurable outputs. ChatGPT can answer questions about your business; this one runs parts of it.

02What if the agent makes a mistake on something important?

Every action that touches money, customers, or external systems goes through a human-in-the-loop approval flow by default. The agent drafts; a human approves. Over time, as eval scores prove out, you can lower the bar for low-risk actions.

03Where does my data live?

Your cloud (AWS, GCP, Vercel, Supabase) or our managed environment — your call. We use your LLM API keys (BYOK), so your prompts and outputs never touch our infrastructure. Enterprise VPC deployment available.

04How much does it cost to RUN per month after launch?

Depends entirely on volume — typical small-business agents run $50–$400/month in LLM costs. We give you a cost forecast in week 1 and put a monthly cap in place so you never get surprised.

05Can I add new tools or processes later?

Yes — that's what the Operations Retainer is for. Or your team can do it themselves; the operations playbook covers it.

06Do you do desktop installs?

No, by default. Desktop installs mean you can't push fixes, security becomes harder, and support gets messy. Cloud-hosted with SSO is the standard. If you need on-prem for compliance reasons, that's an enterprise add-on.

// engage

Ready to scope AI Agent Build?

Book a 30-minute discovery call. No pitch deck. We'll either confirm fit and send a proposal, or tell you straight that this isn't the right move.

Book a Discovery Call Request custom pricing ls services/

automation system

From offer to operating system.

AI Agent Development is presented as a real engagement, not a generic service page: the surface, backend shape, delivery artifacts, and conversion path are all visible before the first call.

Scope AI Agent Build

price

from $2,600

timeline

4 weeks

tier

flagship

Living architecture

Scope ⇄ Ship

The page now exposes how the engagement moves from buyer pain to production artifact, then into measurement and next-step routing.

Scope AI Agent Build

01Discovery + agent designProcess mapping with your team. Identify the workflows the agent will own. Design the tool library, knowledge base structure, and eval criteria. Lock the scope.
02Build — runtime + toolsStand up the agent runtime, wire the tool library to your stack, ingest your SOPs into the knowledge base. First end-to-end run on test data.
03Evals + dashboardBuild out the eval harness with real cases from your business. Stand up the operations dashboard. Wire human-in-the-loop approval flows on high-risk actions.
04Pilot + handoffSoft-launch with one team, monitor evals and dashboard, tune prompts. Documented playbook + 60-minute training session + 30 days Slack support.

Conversion path

Surface ⇄ System

01
Diagnose
Confirm the real automation constraint, current surface, and business goal before writing code.
02
Design the system
Turn the offer into screens, data, workflows, ownership boundaries, and a measurable delivery plan.
03
Ship the artifact
Deliver AI Agent Build as working code, docs, dashboards, or launch assets your team can actually use.
04
Route the next move
Decide whether the work becomes a one-time delivery, a care plan, or a larger product build.

Proof assets

Real only

Asset slot

Service proof visual

Add a real screenshot, deliverable preview, or dashboard capture from a shipped engagement when approved.

pending real proof

Verified asset

Founder/operator photo

Real founder photo reinforcing principal-led delivery.

live

Asset slot

Client quote or logo

Add only permissioned testimonials or logos tied to this service category.