Blash AI is the artificial-intelligence division of Blash Advisory, a London-headquartered corporate finance and advisory firm specialising in AI workflow automation, serving operators, corporates and funds across the UK, EMEA and the Far East.
We connect AI to the tools your team already lives in: inboxes, CRMs, spreadsheets, databases and finance systems. The system classifies, routes, drafts, summarises and updates, so people are no longer the copy-paste layer.
We build automation for the Monday morning when a real enquiry lands at 9pm on a Saturday and someone needs to respond before it goes cold, not for a demo. The work is fixed-fee and measured against the loaded cost of the hours it currently burns.
We name the workflow rather than sell a model. These are the jobs that pay back first.
Every automation we ship has the same skeleton: a deterministic backbone with AI only at the judgement steps. Classification, extraction and drafting are model calls. Routing, retries, logging and the audit trail are plain code. That split is why the system keeps working when a model has a bad day, because the AI step fails into an exception queue instead of silently corrupting your CRM. A real example: short-let payout reconciliation, where every payout email is parsed and matched against the booking ledger, and mismatches are queued with the money at risk attached. The first month surfaced £12.4k of potential mismatches a human review had missed.
Anything that sends money or messages out of the business gets a human approval step on day one. Autonomy is earned with an error-rate record, not assumed. Every workflow ships with monitoring, so you can see what ran, what it decided, and what it refused to decide.
The business stopped losing high-intent enquiries while engineers were on site, and the owner received quote-ready job summaries instead of raw missed calls.
Negotiators started each morning with qualified viewing requests, not a missed-call list and an inbox backlog.
Tenant requests became structured jobs, with cleaner contractor handover and far fewer repeated follow-up emails.
Intake, classification, document extraction, summaries, lead routing, CRM updates, support triage, report drafting and follow-up reminders are the common ones.
Trigger-action tools are right for simple, deterministic hops between two apps. The moment a step needs judgement, such as reading a document, deciding what it is, and drafting a reply, you need an AI layer. We use the simplest reliable approach for each step.
A single workflow typically ships in two to four weeks: one week mapping, one to two building, the rest monitoring against real traffic with a human approving outputs until error rates earn autonomy.
Every build is a fixed fee, with the scope agreed before work starts. The honest comparison is the loaded cost of the hours the workflow currently burns every month. The engagements page sets out how the four builds are structured.
It fails loudly into an exception queue rather than acting. A person reviews only the exceptions, and the audit trail records every decision.
We work with leaders who want AI to move revenue, response time and admin load, not a slide deck. Every recommendation ties to one measurable number.
We build agents that follow your written procedures, use the tools your team uses, and escalate the cases that need a person. Reliable autonomy, earned step by step.
When off-the-shelf tools cap out, we build the software that fits your workflow, data and process: internal apps, dashboards, integrations and automations. Code you own.
We build voice systems that pick up, qualify, book and follow up, then log everything to your CRM and escalate the calls that need a person.
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