Where it breaks.Where we begin.
Nobody calls an engineering firm because they want software. They call because something is straining. Five challenges, each described from the inside: what it looks like, what is actually going on, and what changes.
Growth is outrunning the tools.
You know it when
Every new customer adds work somewhere a person is quietly absorbing it.
The same data gets typed into three systems, and they disagree.
A key process lives in one person's head or one spreadsheet.
Nothing is broken, exactly. It works as long as people keep carrying it.
What is going on
This is the dangerous kind of problem, because it does not look like a crisis. It works until the person absorbing the load leaves, or the volume doubles, or a customer notices that the calendar and the record disagree. The load grows with every new customer. The tools don't.
What we do
We start where the pain is sharpest, usually one workflow, and build the platform that replaces the patchwork around it, one workflow at a time. The systems you already depend on stay where they are; the platform synchronizes with them, so a record is entered once and is correct everywhere. Capacity is designed to stay ahead of demand and load-tested well beyond it.
What changes
Staff time goes to customers, not re-keying.
One record, correct everywhere.
Capacity that scales ahead of demand, not behind it.
A platform that grows with the business instead of being replaced by it.
By the numbers
- The average enterprise runs 957 applications, 27% of them integrated. IT teams spend 36% of their time building custom integrations. Salesforce / MuleSoft, 2026 Connectivity Benchmark
The CRM nobody trusts.
You know it when
Pipeline lives in Salesforce; the truth lives in a spreadsheet.
Reports get rebuilt by hand before every board meeting.
Integrations run on exports, imports, and someone remembering.
The admin backlog is longer than the roadmap.
What is going on
Salesforce was bought to be the system of record and configured until configuration ran out. Past that line the work is engineering: custom code, real integrations, data cleansing. Most orgs stall there. The symptom is distrust. The cause is data that arrives dirty, late, or by hand.
What we do
We treat the org as a system, not a settings page: fix the data model, build the integrations that keep every system agreeing, write the Apex and Lightning components where configuration could not, and clean the data so the reports are believable. Then we keep the org healthy, because trust is lost again the first time the numbers slip.
What changes
One customer record, trusted by sales, service, and finance.
Reports nobody rebuilds by hand.
Integrations with no human in the middle.
An org that stays fast as the record count grows.
By the numbers
- Data leaders estimate that 26% of their organization's data is untrustworthy and 19% is siloed or unusable. Salesforce, State of Data and Analytics 2025
The rewrite you're dreading.
You know it when
Every change carries a risk nobody can quantify.
The engineers who built it are gone, and the documentation went with them.
Performance degrades a little more each quarter.
You've been quoted a full rewrite, and you don't believe the timeline.
What is going on
The platform that got you here was built for a business a fraction of this size, and it has been carrying decisions it was never designed for. A big-bang rewrite is a large IT project by definition, and large IT projects are where budgets go to die: the U.S. government, with every resource available to it, had completed three of the ten legacy modernizations it flagged as critical in 2019 by 2025. The system is already telling you where it breaks. The job is to listen before your customers do.
What we do
We read the system before we touch it: load, data, failure modes, the parts that actually matter. Then we replace it in slices, the riskiest and most valuable first, behind interfaces that keep the business running throughout. Every slice ships stress-tested and documented, so the new platform never becomes the next one you dread.
What changes
The business keeps running through the whole transition.
Risk becomes a list, not a feeling.
Performance you can measure improving.
A codebase your next engineer can read.
By the numbers
- Of more than $100 billion in annual federal IT spending, 79% goes to operating and maintaining existing systems. Of ten critical legacy modernizations flagged in 2019, three were complete by 2025. U.S. Government Accountability Office, GAO-25-107795 (July 2025)
An AI mandate, and no plan.
You know it when
The board wants AI in the business; nobody has said where.
A pilot demoed well and never reached production.
Real questions about your data, your customers' data, and your regulators are unanswered.
Vendors are pitching platforms. You need a result.
What is going on
The distance between a demo and production is accuracy on your data, safety with your customers', an audit trail for your regulators, and a cost per task lower than the person it is helping. None of that is prompting; all of it is engineering. When RAND interviewed 65 practitioners about why AI projects fail, the leading causes were the wrong problem or metric, missing data, technology-first thinking, and no infrastructure to deploy. Not one of them is a model problem. And in a fair number of cases, the honest answer is that a rules engine or a clean integration would solve it with no model in the loop.
What we do
We find the workflows where AI actually pays off (high volume, well defined, a human bottleneck, a way to check the output) and build for production from the first day: your data under your control, evaluation so accuracy is a measured number, guardrails and a human in the loop where the cost of error is high, and audit logging your compliance team can read. Where AI is not the answer, we say so.
What changes
Accuracy is a number you can show the board.
Your data stays under your control.
Cost per task is known before you scale.
It survives the model upgrade after next.
By the numbers
- Only 25% of organizations have moved even 40% of their AI pilots into production. Only 21% have a mature model for governing agents. Deloitte, State of AI in the Enterprise 2026
- Across roughly 5,000 practitioners, AI adoption raised software delivery throughput and reduced delivery stability. Speed without testing shows up as instability. DORA, 2025 State of AI-assisted Software Development
- The leading root causes of failed AI projects: the wrong problem or metric, missing data, technology-first thinking, inadequate infrastructure to deploy, and problems too hard for AI. RAND Corporation (2024)
Compliance you have to prove.
You know it when
Legal keeps asking where the data lives and who has touched it, and nobody has a real answer.
Every vendor says “compliant.” None of them can show you how.
One audit finding would cost more than the whole project.
If it goes down, it is not a support ticket. It is a patient, or a cardholder.
What is going on
Compliance that gets bolted on is compliance that fails the audit. Encryption, access control, and audit logging have to be architecture, decided before the first line of production code rather than checked off at the end. Most compliance is claimed, then audited. The order has to reverse.
What we do
We have built PCI-compliant payments infrastructure that carried a company to an Inc 500 exit, and HIPAA-compliant AI agents with encrypted verification and audit logging. The pattern is the same each time: the controls are designed in during Discovery, the audit trail is a first-class feature rather than an afterthought, and security testing happens before the audit, not after the finding.
What changes
Compliance you can prove, not just claim.
An audit log your compliance team can actually read.
Encryption and access control decided in Discovery, not patched in later.
Security tested before the audit, not after the finding.
By the numbers
- The global average cost of a data breach reached $4.99 million in 2026, a record. Only 37% of breached organizations encrypted sensitive data both at rest and in transit. IBM, Cost of a Data Breach Report 2026
- HIPAA civil penalties now run up to $2,190,294 per calendar year for each category of violation. HHS, Federal Register, January 28, 2026
Yours is different.They all are.
These five are patterns, not a menu. Every real challenge is some mix of them, plus the parts that are only true of your business. Discovery is where we find out which, and it ends with a written price and date, or a plainer path to the same result if one exists.
How Discovery works
Tell us whereit's straining.
The platform, the CRM, the launch, the AI mandate: whatever is carrying more than it was built for. Your free consultation is a working session, not a sales call: honest questions and a point of view, not a brochure.
hello@amtal.dev- Response time
- Within one business day
- Engagements
- Open