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AI / Automation Solutions

Workflows that work, without the demo-ware

We build the unglamorous AI: invoice parsers, lead routers, knowledge assistants, content pipelines. Tied into your stack, observed in production, and shut off cleanly the day they stop earning their keep.

OpenAI · Anthropic · Vercel AI SDK RAG over your data Eval harness, not vibes Cost dashboards from day 1

tengenx · ai workflow

Live

AI workflow stack

Models · Retrieval · Tools · Evals · Cost

Models

OpenAI Anthropic Local (Ollama)

Retrieval

pgvector Postgres FTS Reranker

Tools / actions

CRM write-back Slack / email Webhook router

Eval & guardrails

Golden eval set Prompt versioning Cost / latency budget

Eval pass-rate

≥95%

P95 latency

<3s

Cost / task

Tracked

70%

Manual triage time removed in a typical ops automation

$0.0X

Cost-per-task tracked per workflow

Eval-gated

No release without a passing eval set

Where this fits

Built for the moments you can't postpone

We don't take work just to take work. This service exists because the problems below are the ones we keep being hired to solve, and the ones we've shipped through more than once.

  • Ops team is drowning in repetitive triage that doesn't need a human brain
  • Internal documentation is sprawling, search and 'ask' don't work
  • Sales / support runs on copy-paste from a rats' nest of templates
  • Tried building it in n8n / Zapier, it broke as soon as edge cases hit
  • Have an AI demo that nobody trusts in production
  • Want to ship AI features but the legal / compliance posture isn't clear

What we ship

Solutions, not slide decks

Each line below is a real deliverable shipped on past engagements, with an honest scope and a metric where it makes sense.

01 / Scope

RAG knowledge assistant

An assistant that actually knows your business. Ingestion pipeline, embeddings, hybrid retrieval, reranking, and a chat surface inside the tools you already use.

Eval-gated before launch

02 / Scope

Document & invoice extraction

Structured data out of unstructured PDFs, contracts, and forms, with confidence thresholds and a human-in-the-loop queue for edge cases.

Cuts manual entry ~70%

03 / Scope

Lead routing & lifecycle

Inbound classifier that scores, routes, enriches, and writes back to your CRM. No more shared inbox black holes, no more hand-edited round-robin.

04 / Scope

Content & SEO pipeline

Briefs → drafts → human edit → publish, with brand voice tuned per template and SEO surface (schema, internal links) generated alongside the copy.

05 / Scope

Internal copilots

Domain-specific assistants for sales, support, ops, or engineering, embedded inside Slack, your CRM, your dashboard, or a dedicated console.

06 / Scope

Eval & cost guardrails

Golden eval sets, prompt versioning, regression alerts, P95 latency budgets, and cost-per-task dashboards. Treats AI like any other production system.

≥95% eval pass rate

How we work

A delivery rhythm you can forecast

No mystery sprints. Each phase has a real artefact at the end of it, and you'll always know what's coming next.

  1. 01 Week 0

    Use-case pick

    We help you pick a use-case that's high-impact, evaluable, and safe to ship.

  2. 02 Week 1

    Eval first

    Before any prompt, we write the eval set the system has to pass.

  3. 03 Week 2–6

    Build

    Retrieval, prompts, tools, UI, integration, shipped behind a feature flag.

  4. 04 Week 6–8

    Pilot

    Roll out to one team, watch evals, latency, and cost. Adjust before scaling.

  5. 05 Month 3+

    Operate

    Monitoring, regression alerts, prompt updates, and a quarterly model review.

Engagement

Pick the shape that fits, we'll suggest the rest

We don't pretend one engagement model fits everyone. Pick the closest, and we'll right-size on the call.

Industries we ship for

B2B SaaS Financial services Healthcare ops Legal & compliance DTC support Internal IT / ops

Pilot build

One workflow, end-to-end, with the eval set, the dashboard, and the rollout plan. If it doesn't pass evals, you don't ship, and we say so.

  • Use-case + eval set
  • Working pilot in your stack
  • Cost + latency dashboard
  • Rollout / kill criteria

Indicative

$18k–$60k

Timeline

4–8 weeks

Stack

The tools we reach for

We're not religious about tools, these are the ones we know deeply enough to ship and operate without surprises.

Models

OpenAI Anthropic Vercel AI SDK Mistral Local via Ollama

Retrieval & data

Postgres pgvector Pinecone Cohere reranker Tantivy / Meilisearch

Orchestration

Temporal Inngest n8n Cron + queues

Eval & monitoring

Custom eval harness Promptfoo OpenTelemetry Sentry

Surfaces

In-app chat Slack apps CRM widgets Internal consoles

Common questions

Honest answers, no sales theatre

We've been burned by AI demos that don't survive production. How is this different?

Every workflow we ship has a written eval set before any prompt is tuned, a cost-per-task dashboard, a P95 latency budget, and a kill criterion. We treat AI like any other production system, observable, regression-tested, and rollback-able. If a workflow stops earning its keep, we'd rather shut it off cleanly than keep it on life support.

Will our data leave our stack?

We default to your model provider's enterprise / no-training tier (OpenAI, Anthropic) and run retrieval inside your infrastructure. For sensitive data, health, financial, legal, we can run embeddings and inference fully in your VPC, including local models on GPU. We'll be explicit about which boundary your data crosses.

Do you only work in one model family?

No. Most engagements use OpenAI or Anthropic at the top of the stack with smaller / local models for embeddings, reranking, and high-volume tasks. Model choice is part of the eval, whichever model passes evals at the lowest latency / cost wins, and we re-run that decision quarterly as models change.

Can you integrate with our CRM / support tool / data warehouse?

Yes. Most workflows we ship live inside Slack, HubSpot, Salesforce, Zendesk, Intercom, Linear, or a custom internal console, and write back to your warehouse so the impact is observable. If we can't integrate cleanly, we won't pretend we can.

When is AI the wrong answer?

When the task is deterministic and rules-based (classic automation will be cheaper and safer), when the inputs aren't observable enough to evaluate, or when the cost of a wrong answer is higher than the cost of doing it manually. We'll tell you that on the call rather than upsell you a workflow that shouldn't exist.

Ready when you are

Let's automate the right thing .

Tell us about the workflow you'd most like to take off your team's plate. We'll come back with a feasibility read, an eval-set sketch, and a phased plan, usually within a few business days.