Your team is doing work a machine should do.
We map where your team loses hours, build the AI systems that take those hours back, and stay on the hook for what they save.
Most teams lose 8 to 15 hours a week per person to work that repeats: retyping invoices, chasing status, answering the same twenty questions. That is the work we take away.
112
documented automation patterns across 14 industries
2-4 wks
from first call to a pilot running on your data
Fixed
scoped pricing, agreed before we build
Yours
code, prompts and infrastructure, on handover
The same work
comes back every week.
You did not hire an operations manager to rekey supplier invoices, or your best closer to chase paperwork. The repetitive layer grows anyway, and it lands on the people you can least afford to lose to it.
It hides in inboxes
The process lives in an email thread, a spreadsheet and someone's head, not in your software. Generic tools cannot reach it there.
It scales with revenue
Every new customer adds tickets, invoices, reports and reconciliations. Growth costs you headcount before it pays you margin.
It is invisible on the P&L
No line item says 'four days a month retyping PDFs'. The cost sits inside salaries nobody questions.
It burns your best people
Capable people quit roles that turn into 60% admin. Replacing one of them costs more than the automation would have.
Eight building blocks we combine into one working system.
A typical engagement uses two or three. We pick them by payback period, using your volumes and your salaries.
AI agents that do the work
Agents that read a request, look it up in your systems and finish the task, then escalate the cases they should not decide alone.
- Customer, sales and internal support agents
- Tool use against your CRM, ERP and databases
- Explicit escalation rules and human approval gates
- Full transcript and decision logging
Document and email intelligence
Invoices, contracts, forms, drawings, claims and the PDF attachments filling your shared inbox, turned into structured data your systems can read.
- Extraction into your schema with validation rules
- Classification, routing and duplicate detection
- Confidence thresholds with a human review queue
- Works with email, scans, portals and legacy formats
Voice and messaging automation
Answer every call and message, at any hour, in the channels your customers already use, with a clean handover to a person when it matters.
- Inbound voice agents that book, reschedule and qualify
- WhatsApp, SMS, web chat and social inboxes in one place
- Instant lead response measured in seconds
- Live transfer with the full context attached
Knowledge assistants over your own data
Ask your policies, contracts, manuals and past work a question. Answers come back with citations, inside the permissions each person already has.
- Retrieval grounded strictly in your documents
- Citations on every answer
- Permission-aware so people see only what they should
- Slack, Teams, web or in-product delivery
Workflow orchestration
The multi-step processes that cross five systems and run today on someone remembering to start them.
- Event-driven pipelines with retries and alerting
- Approvals, thresholds and audit trails
- Integration with the tools you already pay for
- Monitoring so a silent failure is impossible
Reporting that writes itself
Reports pulled, analysed and written up on a schedule, so the numbers arrive with the explanation attached.
- Automated data pulls across platforms
- Anomaly detection with plain-English alerts
- Client-ready and board-ready formats
- Commentary drafted, human approved
Automation audit and roadmap
Two weeks inside your operation tracing where the hours go, ending in a costed roadmap you can run with us or without us.
- Process mapping and time-cost quantification
- Feasibility, risk and data-readiness assessment
- Ranked backlog by payback period
- Credited against your build if you go ahead
Custom AI product engineering
AI features inside your own software, built to production standards by people who have shipped them before.
- In-product assistants and copilots
- Model selection, evaluation and cost control
- Guardrails, evals and regression testing
- Handover and documentation, or ongoing ownership
Find your industry and the hours it loses.
112 documented automations across 14 sectors, each with the manual process it replaces and the outcome to expect.
Four phases, eight weeks, one working system.
Your first workflow runs on real data inside two months. You decide what happens next from what it saved, not from a slide.
Audit
We sit with your team and follow the work: which tasks repeat, how long they take, what they cost, and which ones a machine can do. You keep the ranked list and its payback periods whether or not you hire us.
Pilot
We build the highest-payback workflow first, on your real data, in your real systems. It runs alongside your team so you can compare its output against theirs before anyone depends on it.
Deploy
We harden the integrations, set the guardrails, wire in approvals and train the team. The dashboard then shows what the system handled, what it escalated and what it saved.
Run and expand
We monitor, tune and keep pace with your process changes and with the models. Once the first workflow pays for itself, we work down the roadmap.
Four things we hold ourselves to.
We start with the task that costs you most
The first question in every engagement is which repeated task burns the most hours a month. If nothing has a payback under six months, we say so and turn the project down.
Pilots run on your real data
Synthetic data hides the hard parts: misspelled supplier names, the scanned fax, the customer who writes in three languages. We start where the mess is.
Guardrails are part of the build, not an afterthought
Scoped permissions, confidence thresholds, escalation rules, logging and human approval on anything consequential. An agent that is unsure stops instead of guessing.
You own what we build
Code, prompts, evaluation suites and infrastructure sit in your own accounts. No black box, and no per-seat surprise in year two.
Three ways to start. You get the price first.
No hourly meter, and no discovery phase that bills for six weeks before anything runs.
Automation Audit
Fixed fee, credited against a build
2 weeks
Best when: You know there is waste but not where it is
Pilot Build
Fixed project fee
4-8 weeks
Best when: One painful workflow you want gone
Automation Partner
Monthly retainer
Ongoing
Best when: You want a roadmap executed, not a one-off
What people ask before they commit.
Audits are a fixed fee and are credited against a build. Single-workflow builds typically land in the low five figures, multi-workflow programmes higher, and ongoing running and support is a fixed monthly fee. You get the number before we start, not a rolling hourly bill.
A first pilot on your real data usually runs within two to four weeks of the kickoff call. Full deployment with integrations and training normally lands between weeks four and eight.
No. Smaller teams often see the fastest payback, because one person is doing five jobs and every hour returned is visible immediately. We scope single-workflow projects specifically for this.
Off-the-shelf tools assume a generic process. Adoption usually fails at the integration boundary, where the tool cannot see your systems. We build around the process you actually run and wire it into the systems you already use.
Most of our clients redeploy people rather than remove them: the same team handles more volume, or moves off data entry onto work customers notice. We are happy to be direct about it in the audit, because pretending otherwise makes adoption fail.
Tell us what your team keeps doing by hand.
Two questions and your details. You get a straight answer on whether we can automate it, what it takes and what it costs. If it is not worth doing, we say so.
An engineer reads it and replies
A scope and cost range on the first call
No obligation and no drip campaign
Prefer email? contact@tinkerberrylabs.com