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AI integration

AI past the demo

Voice agents, assistants and semantic search — grounded in your data, wired into your stack, and running in production. Not another pilot that never ships.

See AI cases
Diagnosis

Where most AI stalls

One gap at a time — swipe through the six we see most.

  1. 01 / 06 · Pilot purgatory
    Problem

    A demo that never ships

    The proof-of-concept wowed everyone, then sat in a notebook for a year. The model was never the hard part.

    Solution

    Production from day one

    We build for real traffic — auth, error handling, monitoring — so it runs in production, not a demo tab.

    See it shipped — Up-Struct
  2. 02 / 06 · Made-up answers
    Problem

    A model that makes things up

    Ask about your business and it invents a confident, wrong answer — guessing from the open web, not your data.

    Solution

    Grounded in your data

    We wire it to your records with retrieval and tools, so it answers from your data — and says when it’s unsure.

    See it shipped — SQUEAK E CLEAN
  3. 03 / 06 · All talk
    Problem

    A chatbot that only chats

    It describes what to do but can’t do it — every answer ends with a human doing the actual work.

    Solution

    Agents that take action

    We give it tools — it updates the CRM, sends the message, books the call. It does the step, not just narrates it.

    See it shipped — SQUEAK E CLEAN
  4. 04 / 06 · Bolted on
    Problem

    AI that can’t see your stack

    A clever model with no access to your tools is a party trick — it can’t read the ticket or update the record.

    Solution

    Wired into your tools

    We connect it to your CRM and phones — it works inside the systems your team already runs.

    See it shipped — EclipseGroup
  5. 05 / 06 · Black box
    Problem

    A black box you can’t trust

    When you can’t see why it answered, you can’t put it near anything that matters.

    Solution

    Traceable, with a human in the loop

    Every action is logged, and high-stakes steps wait for a human. You can audit exactly what it did.

    See it shipped — Up-Struct
  6. 06 / 06 · Rented AI
    Problem

    Renting AI you don’t control

    Your prompts, data and logic live inside someone else’s product — and leave when their pricing changes.

    Solution

    Built on your keys

    We build on your keys and your data. The model stays swappable; the product is yours.

    See it shipped — SQUEAK E CLEAN
Inside AI integration

AI takes many shapes

A sample of what we’ve shipped — and if your use case isn’t here, we’ll still build it.

  • Inbound + outbound calls
  • Human-like cloned voice
  • Sub-7-second response
ClaudeElevenLabsTwilioShipped atUp-Struct
  • Plain-English queries
  • Acts on your CRM
  • Scoped, secure access
ClaudeMondayMakeShipped atSQUEAK E CLEAN
  • Search by meaning
  • Opportunity matching
  • Whole-catalog recall
ClaudepgvectorPostgreSQLShipped atSQUEAK E CLEAN
  • Automatic transcription
  • Summaries + extraction
  • Logged to the CRM
WhisperClaudeAircallShipped atEclipseGroup

Examples, not a menu. Tell us where AI should pay off — we’ll build the narrow thing that ships, not a demo that promises everything.

Tell us the problem
Ways to work

Four ways to work with us

An AI build doesn’t start the same way twice. Pick the engagement model that fits your situation — not ours.

When to choose
How we start
  1. Discovery call
  2. Scope in 2 weeks
  3. 4–12 week build
When to choose
How we start
  1. Immersion sprint
  2. Phased roadmap
  3. Parallel tracks
When to choose
How we start
  1. Submit a task
  2. Scoped in 24h
  3. 1–2 sprints
When to choose
How we start
  1. Dedicated channel
  2. Weekly sync
  3. Guaranteed capacity
Stack

The right model for the job

No single-model dogma. We pick the model — plus the boring infrastructure around it that makes it reliable — and keep it swappable as better ones ship.

Models & reasoning
ClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisperClaudeGPTWhisper
Voice
ElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircallElevenLabsTwilioAircall
Data & retrieval
pgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePythonpgvectorPostgreSQLSupabasePython
Glue & delivery
MondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScriptMondayMakeVeriffNext.jsTypeScript
Insights

What the work taught us

Hard-won notes from shipping AI to production — the difference between a demo and something you can put a customer on.

Most of an AI build isn’t the model. It’s wiring it into your tools and keeping it stable in production.

Grounded in your records, the model answers from your own data, not a guess.

An agent earns its keep when it takes action in your systems, not just answers questions.

Build on your own keys and data, and a newer model becomes a swap, not a rebuild.

Selected impact

Where it moved the needle

Three AI builds — three different kinds of win. Open any folder for the full story.

FAQ

Answers before you ask

We only build AI we’d put in front of your own customers. If a use case won’t reliably work, you hear it on the first call — before you spend a dollar building it.

A working prototype on your data in 2–3 weeks, not a six-month research phase. You judge it on real output, early — and decide from there.

We ground it in your data and limit it to verifiable actions, so answers trace back to your records — not the open web. On anything high-stakes, a human approves before it acts.

You own it — your keys, your data, your code. No per-seat AI fees, and nothing locked to us.

No. We use API tiers that don’t train on your data, and keep anything sensitive in your own systems.

Good — we keep the model swappable, so a better or cheaper one is a quick upgrade, not a rebuild.

Let's talk

Tell us where AI should
earn its keep

A 30-minute discovery call. We pressure-test the use case, sketch the agent live, and tell you whether it's worth building — straight.

— or —[email protected] ↗