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hello@adherelabs.com · San Ramon, California · Serving clients across North America
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02 — Build

The middleware between systems that were never meant to meet.

Internal tools, dashboards, data pipelines and integration layers. We connect the CRM, the scheduling system, the accounting package and the twenty-year-old database — and turn the copy-paste job between them into something that runs itself.

What this is

Somebody is currently being the integration.

Every operating business has a person who exports a report on Monday, reformats it, uploads it somewhere else, and fixes the four rows that never match. They are the API. They are also on vacation next week, and they are the only one who knows which rows to fix.

i.

Internal tools

The screens your operations team needs and no vendor sells: dispatch boards, approval queues, quoting calculators, reconciliation views. Purpose-built for one workflow instead of configured around a product that almost fits.

ii.

Dashboards and reporting

One number, one definition, one place. We consolidate the sources, agree the definitions in writing, and build reporting that leadership trusts enough to act on without a side conversation about whose spreadsheet is right.

iii.

Data pipelines

Scheduled and event-driven movement between systems, with validation, deduplication, retries and a record of what ran. Not a script on somebody's laptop that fails silently over a long weekend.

iv.

Integration middleware

A layer that speaks to each system in its own language and presents one consistent interface to everything else. Add or replace a vendor without rewriting every connection you have.

What you get

Connections that hold under load.

01

The integration layer

RESTGraphQLWebhooksOAuth 2.0Queues

Point-to-point connections multiply badly: six systems wired directly to each other means fifteen relationships to maintain, and every vendor change breaks several at once. We build a layer in the middle with a canonical model of the entities that matter to you — customer, job, invoice, asset — and adapters that translate each system into it. Failures are handled honestly: retries with backoff, dead-letter queues for what cannot be processed, idempotency so a replayed webhook does not create a second invoice, and alerts that reach a person instead of a log file.

  • Canonical data model agreed across the systems in scope
  • Per-system adapters with credential handling through OAuth 2.0 or scoped keys
  • Retry, backoff, dead-letter handling and idempotent writes
  • Field-level mapping documented so future changes are safe
  • Monitoring and alerting on every sync path
02

Internal tools and dashboards

PostgresSupabaseRole-based accessAudit trail

We build these the same way we build customer-facing software, because internal users deserve interfaces that do not fight them and because a mistake in an internal tool costs just as much. Permissions are real, actions are logged, destructive operations are confirmed and reversible, and the screens are designed around how the work is actually sequenced rather than around the shape of the database.

  • Task-shaped interfaces designed with the people who use them daily
  • Role-based access with an audit trail on privileged actions
  • Consolidated reporting with definitions agreed and documented
  • Bulk operations with preview, confirmation and undo where possible
03

Legacy modernization and migration

Strangler patternDry runsReconciliationRollback

Big-bang replacements fail for the same reason every time: the old system contains a decade of undocumented behavior that nobody can fully describe until it stops happening. We prefer to wrap the legacy system in an interface, move one workflow at a time, and shut the old path off only once the new one has carried real traffic. When a full migration is right, it is rehearsed repeatedly against a copy of production with record counts and financial totals reconciled after every pass, and a documented rollback ready before cutover day.

  • Assessment of what to keep, wrap, replace or retire, with costs attached
  • Incremental migration path so value lands before the project ends
  • Repeated dry runs with reconciliation reports you can check yourself
  • Documented exceptions — the records not migrated, and why
  • Rollback plan rehearsed, not improvised
04

Data pipelines and quality

n8nPostgresScheduled jobsValidation

Automation inherits the quality of the data it reads. Before anything clever is built on top, we handle the unglamorous work: deduplication rules, normalized phone numbers and addresses, consistent identifiers across systems, validation at ingestion, and quarantine for records that fail rather than silent dropping. Every run leaves a trace, so when a number looks wrong you can find out exactly what produced it.

  • Scheduled and event-driven pipelines with full run history
  • Deduplication, normalization and identity resolution across sources
  • Validation at ingestion with quarantine for failed records
  • Alerting when a pipeline stalls, not a discovery a week later
How it connects to the AI layer

This is the layer agents actually stand on.

An agent is only as good as the systems it plugs into. Everything on this page is what turns a language model into something that can change the state of your business — safely, with permissions and a record of what it did.

05

Tools, permissions and audit for agents

MCPScoped authn8nHubSpotSalesforceQuickBooks

Once the integration layer exists, exposing it to agents is a small, controlled step. Each capability becomes a defined tool with a narrow scope: look up an account, check availability, create a job, issue a credit up to a limit. Access is granted per agent through scoped credentials and MCP rather than by handing over an admin key, high-consequence actions require confirmation or a human approval step, and every call is logged with its inputs and its result. That is what makes automation defensible when finance or compliance asks who did what.

It also runs in the other direction. Events from your systems — a job completed, an invoice overdue, a contract nearing renewal — become triggers that start workflows without anyone watching a screen for them.

  • Agent-facing tools with narrow, explicit scopes over your systems
  • Scoped credentials and MCP access instead of shared admin logins
  • Approval gates on financial and irreversible actions
  • Complete audit log of every agent read and write
  • Event triggers published from your systems into automation workflows
n8nZapierMakeRESTGraphQLWebhooksOAuth 2.0MCPPostgresSupabaseAWSGoogle CloudHubSpotSalesforceServiceNowQuickBooksStripeShopifySlackNotion
The shape of it

One layer in the middle, instead of a web of wires.

Fig. 01 — Middleware bridge
CRM REST + webhooks Scheduling system Nightly export Legacy database Direct query Integration layer Map · validate · retry One canonical model Reporting Agents & workflows
Each system keeps its own format; only the layer in the middle has to understand all of them. Replacing the scheduling vendor means rewriting one connector rather than every relationship it had. The canonical model is also what makes the right-hand side possible — reporting and agents read one definition of a customer, a job and an invoice instead of reconciling three.
How we work

Map it, connect it, then watch it.

Phase 01 — Audit

Trace the real path

We follow one record end to end through every system and every person who touches it. The gaps, the re-keying and the silent failures surface fast, and you get them written down with a priced plan.

30-min call · roadmap delivered
Phase 02 — Build

One connection at a time

The highest-cost manual handoff goes first, runs in parallel with the old process until it proves itself, then takes over. Value lands in weeks rather than at the end of a long program.

Typically 2–8 weeks per flow
Phase 03 — Run

Monitor and extend

Alerting on every sync path, a dashboard showing what ran and what failed, and someone paying attention when a vendor changes an API. Then the next flow, and eventually the agents on top.

Ongoing partnership
Common questions

Before you ask.

One of our systems has no API. Can it still be connected? +

Usually. Before resorting to screen automation we look for a database we can read, a scheduled export, an SFTP drop, a reporting endpoint or an email the system already sends. One of those exists far more often than vendors admit. Where nothing does, we automate the interface carefully and monitor it closely, and we tell you plainly that it is the fragile option.

Should we replace the legacy system or work around it? +

Work around it more often than people expect. A stable system that does its job badly but predictably is usually cheaper to wrap in an integration layer than to replace. Replacement earns its cost when the system blocks something you must do, when support has ended, or when its data model makes every new process expensive. We give you both numbers before you decide.

Is this the same as using Zapier or Make? +

It overlaps, and we use those tools where they fit. They stop fitting when volume climbs, when a failure needs to be retried safely rather than silently dropped, when a transformation gets complicated, or when the per-task pricing quietly exceeds the cost of hosting the same flow yourself. We build the durable version, often on n8n in your own infrastructure.

How do you keep a migration from losing data? +

By rehearsing it. We run the migration repeatedly against a copy of production, reconcile record counts and financial totals after every pass, and keep a written list of the exceptions we chose not to migrate and why. The real cutover is the rehearsal you have already done several times, with a rollback path prepared in advance.

Who maintains the integration afterward? +

You can, and we can. Everything runs in your accounts with documentation, monitoring and alerting included, so your team is able to operate it. Most clients keep us on a support plan because vendor APIs change without notice and someone has to notice first. Either way, nothing is hidden inside a system only we can reach.

Do we need this before adding AI agents? +

Almost always, in some form. An agent needs a reliable way to read current data and write results back, with permissions and an audit trail. That is exactly what an integration layer provides. Skipping it produces agents that sound impressive in a demo and cannot change anything in your business.

The quiet risk

The process only one person understands
is the one that stops.

Start here

Name the two systems that still don't talk.

Thirty minutes, no charge. We will trace one record through your stack, show you where the manual hours go, and send you a prioritized plan for connecting it.

Roadmap delivered · whether or not you build with us