agent.ops@ v3.4.1
Internal agents
SyncprodOps bots, sales-call summarizers, lead enrichment, content drafters, internal admin tools. Models routed by task. Human-in-the-loop where it matters.
Signature
ops: (task: Brief) → Result<Action[]>stack · Claude Agent SDK · n8n
Model
Claude Opus 4.7
Latency · p95
2.1s
Cost / call
$0.018
Eval pass
96.2%
agent.rag@ v2.7.0
RAG support chat
StreamingprodCustomer-facing chat with retrieval over your knowledge base. Confidence thresholds, citation surfacing, fall-back to human. Deflection metrics on the dashboard.
Signature
rag: (msg: Msg, ctx: Conv) → Stream<Reply>stack · pgvector · LangGraph
Model
Claude Sonnet 4.6 · pgvector
Latency · p95
1.4s
Cost / call
$0.014
Eval pass
94.1%
agent.voice@ v1.9.0
Voice agents
RealtimeprodInbound qualification, outbound sales, appointment booking. Sub-600ms latency. Real-time transcription, structured output, CRM-side write-back.
Signature
voice: (audio: Stream<PCM>) → Stream<Turn>stack · Vapi · Retell · WebRTC
Model
Haiku 4.5 · Vapi · Retell
Latency · p95
560ms
Cost / call
$0.21 / min
Eval pass
91.8%
flow.automate@ v4.1.2
Workflow automations
AsyncprodForm-to-action chains, CRM enrichment, scoring, nurture cadence, reporting pipelines. n8n self-hosted for engineer-grade control.
Signature
automate: (trigger: Event) → Run<Job>stack · n8n · Make · Zapier
Model
Routed · Sonnet / Haiku
Latency · p95
320ms
Cost / call
$0.004
Eval pass
98.4%
agent.content@ v2.3.0
Content pipelines
Multi-agentprodOne pillar to twelve atoms. Brief, draft, edit, schedule, distribute. Voice-locked to your tone document. AI drafts, senior editor reviews, you ship.
Signature
content: (pillar: Brief) → Atom[12]stack · Claude · n8n
Model
Claude Opus 4.7 · Sonnet 4.6
Latency · p95
4.8s
Cost / call
$0.42 / piece
Eval pass
89.6%
agent.admin@ v1.5.4
Internal LLM admin tools
SyncstagingLightweight web apps backed by LLMs for ops teams. Tag classification, summarization queues, batch-extract jobs, knowledge-base curation.
Signature
admin: (rows: Record[]) → Annotated[]stack · Next.js · Claude
Model
Haiku 4.5
Latency · p95
180ms
Cost / call
$0.0006 / row
Eval pass
95.3%
Claude Agent SDK·n8n·RAG·MCP·Voice·Evals
Production AI agents. Shipped, not pitched.
Senior AI engineering. Real agents in production, not slideware. Internal ops bots, RAG-backed support chat, lead enrichment, content pipelines, voice agents. Built with Claude Agent SDK, n8n, LangGraph, and Langfuse for evals. Code lives in your repo. Token costs pass through transparently.
- 01Senior AI engineer named on day one
- 02Code in your repo, on your infra, your API keys
- 03Evals and tracing wired from day one
- 04Free workflow audit in four business days
Send the workflow. Get the diagram.
Tell us what to automate. Inside four business days you get an agent diagram, an eval plan, a token-cost estimate, the named senior engineer, and a price.
Reply within one business day · Read by a senior engineer
Agent diagram · sanitized snapshot
The pipeline we actually ship.
Five nodes, each with a real latency and a real cost. This is the diagram you get back in your audit, with the exact stack we'd ship for your workflow. Evals run on every node. Tracing is wired before the agent goes live. Token cost is transparent, dashboarded, and yours to inspect.
Diagram v 04 · client-11
- 01
Trigger
Form / Webhook
p95
80ms
cost
$0.001
- 02
Retrieve
pgvector / Pinecone
p95
120ms
cost
$0.0008
- 03
LLM
Claude Opus 4.7
p95
1.4s
cost
$0.012
- 04
Eval
Langfuse / Braintrust
p95
60ms
cost
$0.0003
- 05
Action
CRM / Slack / DB
p95
90ms
cost
$0.0005
Total p95
1.75s
Cost / call
$0.014
Eval pass rate
94.2%
- 47% deflection$0.014 / msg
Support deflection bot
- 12k leads / week$0.008 / lead
Lead enricher
- 640 hrs saved / qtr$0.21 / call
Call summarizer
- 1 pillar → 12 atoms$0.42 / piece
Content pipeline
This is what an audit response looks like. A real diagram, real costs, real evals. No strategy deck.
Send the workflowWorkflow audit · sample from a Q3 onboarding
What we look at before an agent ships.
Every engagement opens with an eight-point workflow audit. Six rows below are pulled from a real onboarding. FAIL items become sprint one. PASS items get held in place.
- FAILHallucination managementNo retrieval grounding. No confidence threshold. No HITL fallback for low-confidence answers.
- FAILObservability and tracingNo tracing wired. Can't inspect prompt, retrieval context, or tool calls. Debugging is a black box.
- WARNEval suiteZero evals. No regression detection between prompt versions. Quality drift goes unnoticed.
- WARNVendor lock-inHardcoded to single provider. No abstraction layer. Migrating away requires a rewrite.
- PASSData residency and securityVendor confirmed not to train on inputs. PII scrubbing in place. Audit log retained 90 days.
- PASSAPI key custodyKeys live in your vault, rotated quarterly. Per-environment scoping. No shared keys in the codebase.
Eight rows like these land in your inbox inside four business days, alongside the agent diagram.
Commission the auditI·Retainer floor
$3,500
/ month + tokens
II·Project pricing floor
$10K+
/ agent build
III·Production gate
Day 01
evals + tracing
IV·From brief to audit
4
business days
Multi-agent build from $50K · Voice agent from $25K · Token cost passthrough, transparent dashboards
agents.registry · production manifest
Six entries in the registry. Each one typed and shipped.
06 / 06 · live · code in your repo
Stack is yours to inspect, swap, or fork. Every entry above is a senior call we can defend in writing — with the eval suite to back it.
Send the workflowWhen the call usually comes in
Three reasons the workflow lands in our inbox.
- Reason 01
You have an ops problem that should be a script.
Sales call summaries, lead enrichment, internal classification, content distribution. All of it manual. The senior AI engineer you wanted to hire wants $300k loaded. We're the bench you bring in instead, shipping production agents inside the first sprint.
- Reason 02
Your team built a Zapier flow and it's breaking weekly.
Twelve steps, three branches, a janky LLM call in the middle, no error handling. We rebuild it on n8n self-hosted with evals, retries, and observability. Faster, cheaper, traceable. Code lives in your repo so your team can take it back any time.
- Reason 03
You're tired of AI consultants who ship slides.
Three months and a strategy deck cost $80k. Zero shipped agents. We do the opposite. Audit lands in four business days, first agent prototype in your repo by day seven, evals wired before production traffic.
The honest comparison
When senior-led AI is the right answer. And when it isn't.
- Senior AI engineer named on the workyesnodependsyes
- Evals + tracing on day onedependsnorareyes
- Code in your repoyesnodependsyes
- Token cost passthrough, transparentn/anorareyes
- HITL fallback wired independsnodependsyes
- Mutual NDA + no-train clausen/anodependsyes
- Fully loaded annual cost$280-400k$60-120k$60-180k$42-180k
- Time to first agent in production10 weeks1 day (fragile)12 weeks1 week
Four principles.
Wired into every agent.
The reasons most AI projects fail are the reasons we put these four principles in the room before any agent goes live.
- PI
You own the prompts, code, and infra
Every prompt lives in your repo, version-controlled. The agent code lives in your repo. The infra runs on your accounts (AWS, Vercel, Railway, your call). Token costs pass through transparently from the provider. We don't resell tokens or hold your API keys.
Principle I - PII
Evals and tracing on day one
Langfuse or Braintrust wired before the first production call. Every prompt change runs against the eval suite. Tracing on every node. You can inspect what the agent did, why it did it, and how much it cost, per request.
Principle II - PIII
Hallucination has a human-in-the-loop fallback
Confidence thresholds enforced on every output. Below threshold routes to a human queue, not a guess. Citations surfaced wherever the agent claims a fact. Retrieval is the default, generation is the assist.
Principle III - PIV
Mutual NDA, no training on your data
Signed before we look at your workflows. Vendor contracts confirmed not to train on your inputs. PII scrubbing in place. Audit log retained on your schedule, not ours.
Principle IV
Operator's mark
You can leave after the first sprint. We'd rather you stay because the agents are paying for themselves.
Eval ledger · v0.1 → v1.0 · 28 days
The cadence is an eval suite. No version ships without it.
Production gate · ≥ 90% pass
- v0.1Day 03
Baseline · zero-shot Claude Sonnet, no retrieval, no HITL.
84 tests · Senior engineer
p951.9sCost$0.01846.2% - v0.2Day 07
Added pgvector retrieval over your KB. Confidence threshold at 0.72.
124 tests · Senior engineer
p951.7sCost$0.01462.8%▲ 16.6 - v0.3Day 12
System prompt rewrite. Voice locked to brand doc. Banned phrases enforced.
188 tests · Senior engineer
p951.6sCost$0.01471.4%▲ 8.6 - v0.4Day 18
HITL fallback wired below 0.65 confidence. Citation surfacing added.
246 tests · Senior engineer
p951.5sCost$0.01382.0%▲ 10.6 - v0.5Day 22
Router added. Haiku for tier-2 queries, Opus for tier-1. Cost halved.
312 tests · Senior engineer
p951.4sCost$0.00987.6%▲ 5.6 - v1.0shippedDay 28
Eval suite past production gate. Rolled out to 100% traffic.
312 tests · Account lead
p951.4sCost$0.00994.2%▲ 6.6
First agent ships to production inside three weeks. Diagram and audit land in four business days.
Start the auditWhat people ask before they let an agent into the stack.
Plain answers about prompt ownership, hallucination management, evals, costs, and how a production AI program actually runs.
Zapier is great for two-tool, low-stakes glue. The moment a workflow needs branching logic, retry handling, audit logs, or LLM calls inside a step, you hit the wall fast. We build the next layer down — custom code with proper observability — and only reach for an LLM when classification or generation is the actual job.
Whichever fits the task. Claude for reasoning and code-adjacent work, GPT-4 for general agents, Gemini for cost-sensitive classification, locally hosted Llama for privacy-sensitive enterprise jobs. We tell you which model and why in the scoping doc, and we keep the choice swappable.
They work. Every build ships with a runbook, monitoring dashboards, and an on-call escalation path. A monthly operating retainer is optional — it covers alerts, edge-case fixes, and model swaps as the providers update. Many teams take it for the first six months and then move ops in-house.
In your infrastructure. Postgres, Supabase, your VPC, your S3 bucket. We never run a multi-tenant database. API keys for the models stay in your environment variables. Everything we build is fully transferable on day one.
Yes. Custom CRMs are a regular engagement — same stack as the automations, with admin pages, role-based access, audit logs, and the workflow automations layered on top. Designed around your team's actual workflow, not adapted from Salesforce.
Every flow has a retry policy, a fallback path, and a Slack alert when both fail. The run log records every invocation with its status and duration. Edge cases that surface in production get added to the test suite. Nothing fails silently.
Still have a question we didn't cover? Ask it in the brief. A senior engineer reads every submission inside one business day.
What happens after you send
Three steps. Four business days.
You send the workflow. The agent diagram and audit land four business days later. Here is exactly what runs in between.
- 01Within 24 hours
A senior replies
Not a coordinator, not an SDR. The senior AI engineer who would run your workflow replies from a real email, confirms scope, and sends the mutual NDA with the no-training clause.
- 02Days 2 to 3
We run the workflow audit
After the NDA is signed, we audit the workflow. Hallucination management, observability, evals, vendor lock-in, data residency, API key custody. Eight points across the agent surface.
- 03Day 04
Diagram and price land
You get the agent diagram, the audit document, an eval plan, a token-cost estimate, the named senior engineer, and a transparent price. Retainer or project, your call.
No follow-up sequence. No drip campaign. If we miss the four-day window, we eat the first sprint.
Start step 01One step
Send the workflow.
We'll send back a diagram.
Inside four business days, you get an agent diagram, a workflow audit, an eval plan, a token-cost estimate, the named senior engineer, and a transparent price. Retainer or project, your call.
- 01Free agent diagram + workflow audit in 4 biz days
- 02Senior AI engineer named on day one
- 03Code in your repo, evals on day one
- 04Token cost passthrough, transparent dashboards
Rather talk first?
Book a 20-minute call with a seniorSend the workflow. Diagram comes back in four.
Five fields. One business day to a senior reply. No follow-up sequence.
Sealed · Read by a senior engineer
Free workflow audit · 4 biz days
Production AI agents, not slides