Services

AI in your workflows — built by people who ship AI products.

Most AI consulting is slideware. We're a product studio: we build and run AI software ourselves, so when we build for you, it's working software — not a strategy deck.

Built for technology-first teams

Our clients are small and mid-size companies that already run on software — SaaS businesses, dev shops, tech-enabled services firms — where the workflows are digital but still rely too much on people doing repetitive, low-judgment work. Not enterprises with 18-month procurement cycles. Not companies that need to be convinced AI is real. Teams that are ready to move.

10–100 people

Small enough that every hour matters. Large enough that workflow problems are real and costing you.

Already on modern tools

Slack, Linear, Notion, HubSpot, Jira — we plug into what you use, not replace it.

Want results, not a roadmap

You need a working pilot in weeks, not a 90-day discovery engagement.

The cost of skipping validation

Most teams build the wrong thing. Then find out after.

Entrepreneurs waste significant time and capital developing products without first validating market interest or actual customer needs. On average, startups burn 6–12 months and $50k–$200k on product development before learning whether the market wants what they're building.

56% of startups fail not because of execution, but because they built something the market didn't need. The fix isn't a bigger team or more runway — it's learning faster, earlier, and cheaply.

6–12 months

Average time burned on unvalidated product development

SaaStr

$50k–$200k

Average capital spent before validating market interest

SaaStr

56%

Of startups fail because they didn't build what the market needs

Demandsage

Weeks, not months

How long our validation sprints take — without touching your roadmap

Outcome.work

Validate the idea. Don't distract the team.

The moment you ask your engineers or product managers to pause what they're building to explore a new idea, you've already paid a cost. Context switches are expensive. Half-finished validation work is worse than none — it creates false confidence without real evidence.

We run the validation work as a dedicated, external sprint. Your core team keeps shipping. We come back with findings, not just opinions — customer interviews, signal from the market, and a clear recommendation on whether to build, pivot, or stop.

Tell us about your idea

What we build

Document intelligence

Invoices, intake forms, support tickets, contracts, handwritten notes — anything your team reads and retypes. We build pipelines that extract the data reliably and route it into the systems you already use, with human review built in where accuracy matters.

→Customer contracts → CRM fields, auto-populated
→Support emails → structured tickets, prioritized and routed
→Vendor invoices → accounting entries, ready to approve
→Onboarding docs → provisioned accounts and tasks

Workflow automation

The glue work between your inbox, Slack, CRM, spreadsheets, and internal tools. We map the workflow, replace the repetitive steps with AI, and leave your team the judgment calls — so they spend time on work that actually requires them.

→Inbound lead triage: qualify, score, and draft the first reply
→Weekly status reports assembled from Jira, Slack, and email
→Customer health monitoring with automated follow-up drafts
→Meeting notes → action items → task creation in your PM tool

Custom AI products

An internal tool or customer-facing feature, taken from idea to shipped software. We validate before building, start small, and iterate — the same way we build our own products. Most pilots are in production within weeks.

→Internal knowledge base with AI-powered search and answers
→Customer-facing document upload with AI extraction and review
→AI-assisted proposal or quote generation for your sales team
→Automated technical documentation from code or specs

Idea validation

Got a new product direction or feature bet you need to pressure-test — but can't pull your core team off what's already shipping? We run the validation work: customer discovery, problem-solution fit, and a clear go/no-go recommendation. Your team stays focused.

→Customer discovery interviews and synthesis
→Problem-solution fit assessment with real target users
→Competitive and market landscape analysis
→Go/no-go recommendation with evidence, not opinions

What this looks like in practice

Illustrative examples of the kinds of problems we solve — the pattern is almost always the same: a repetitive, document- or data-heavy task that a person shouldn't be doing.

20-person SaaS company

The problem

Support inbox was eating two engineers' afternoons. Tickets arrived unclassified, duplicated, and without the context needed to act.

What we built

AI pipeline reads each ticket, extracts product area, severity, and relevant account data, writes a first-draft response, and routes to the right person. Engineers review and send — they don't triage.

~3 hours/day back. Response time cut in half.

B2B dev shop, 35 people

The problem

Weekly client status updates took a senior PM two hours each. Same data, different format, every Friday.

What we built

Automated report that pulls from Jira, Linear, Slack, and GitHub — summarizes the week, flags blockers, and drafts the client email. PM edits and sends.

Friday reports from 2 hours to 15 minutes.

Tech-enabled services firm, 60 people

The problem

New client onboarding required manually reading and extracting data from intake forms, contracts, and ID documents — two days of admin per client.

What we built

Document pipeline extracts and validates fields across all doc types, populates the CRM and project management system, and flags exceptions for human review.

Onboarding admin from 2 days to under 2 hours.

How we work

Assess

A short working session to map your current workflows and find where AI will actually pay off — and where it won't. No deck, no discovery retainer.

Pilot

A small, real pilot on your actual documents and data. You see results before committing to anything bigger. Most pilots take 2–4 weeks.

Deploy

We productionize what works: reliable, reviewed, integrated with the tools you already use. Then we support it.

Proof, not promises

KalendarKid is our own product: it reads messy real-world documents — forwarded emails, photos of flyers, PDFs — and turns them into structured calendar events with human review before anything is committed. That's the exact pattern most businesses need for their own documents. We've already built it once, in production, for paying users.

Talk to us about your workflow →

Have a workflow AI should be doing?

Tell us what your team retypes, re-keys, or copies between systems every week. We'll tell you if AI can take it off their plate — and prove it with a pilot.

Start a conversation