We've been wiring systems together since before "integration platform" was a category.
REST APIs, webhooks, data pipelines, synchronization between CRM, ServiceTitan, Google, Meta and your own databases, custom middleware and automation triggers. The unglamorous layer that decides whether everything above it actually works.
AI is easy to access. Getting your data to it is the hard part.
Nearly every stalled AI project we're asked to rescue stalled here — not in the model, in the plumbing.
A company's operating truth is spread across systems that were never designed to talk: a field service platform, an ad account, a phone system, a CRM, a billing system, a spreadsheet somebody maintains by hand, and a database from two acquisitions ago. Each one is internally consistent. Together they disagree about how many customers you have.
Integration engineering is the work of making them agree — resolving identities, reconciling timestamps, backfilling history, handling the API that rate-limits at the worst possible hour, and doing it reliably enough that management trusts the number on the dashboard. That work is the foundation under AI systems integration, revenue intelligence and every automation on top.
Bluefrog has been doing it since 1997, and building intelligent integration platforms since 2001 — payment systems designed around PCI and NACHA requirements, CRM and workflow infrastructure, real-time alerting, mobile platforms serving thousands of organizations. The protocols changed. The engineering problem didn't.
One integration map instead of nine point-to-point hacks.
Every system connects once, to a middleware layer that owns identity, scheduling, retries and audit — rather than each tool poking holes in every other tool.
SOURCES BLUEFROG MIDDLEWARE CONSUMERS
───────────────────── ──────────────────────────── ────────────────────
ServiceTitan ──REST/OAuth──┐ ┌──────────────────────────┐ ┌── Revenue Intelligence
CRM ──REST────────┤ │ INGEST │ │
Phone / Voice ──webhook─────┤ │ · webhook receivers │ ├── Call Intelligence
Google Ads ──REST────────┼─▶│ · scheduled pollers │──┬───▶├── Rubric Evaluation
Google LSA ──REST────────┤ │ · file / SFTP drops │ │ │
Meta Ads ──REST────────┤ │ ──────────────────── │ │ ├── Custom Dashboards
Web forms ──POST────────┤ │ NORMALIZE │ │ │
SMS / Email ──webhook─────┤ │ · schema mapping │ │ ├── Automation Triggers
MySQL/MSSQL ──SQL/CDC─────┤ │ · identity resolution │ │ │
Legacy / CSV ──batch───────┘ │ · dedupe + validate │ │ └── Answer Hub / Content
│ ──────────────────── │ │
│ STORE │ │ WRITE-BACK
QUEUE + RETRY │ · normalized warehouse │ │ ────────────────────
───────────── │ · full change history │ └───▶ CRM notes / tasks
· idempotency keys │ ──────────────────── │ ServiceTitan records
· exponential backoff │ ACT │ Ad platform signals
· dead-letter queue │ · rules + AI agents │ Alerts / Slack / email
· replay from log │ · scheduled jobs │ Customer messaging
└──────────────────────────┘
OBSERVABILITY: request logs · per-connector health · drift alerts · reconciliation reports
All integrations → · ServiceTitan integration → · Google Ads → · Google LSA → · Meta →
What integration engineering actually includes.
REST & GraphQL APIs
Consuming third-party APIs and publishing our own. OAuth and token lifecycle, pagination, rate-limit budgets, versioning, sandbox-to-production promotion, and clients that fail loudly instead of silently returning empty arrays.
Webhooks & events
Receivers that verify signatures, respond fast, and queue the real work. Out-of-order delivery, duplicate delivery and replay are assumed, not treated as surprises. Every event is persisted before processing so nothing is lost to a bad deploy.
Data pipelines
Scheduled extraction, incremental loads, historical backfill, change-data capture from SQL systems, and transformation into a normalized model that a dashboard or an AI agent can query without knowing where the data came from.
Sync & identity resolution
The hard one. The same customer exists as a phone number, an email, a CRM ID and a service address. We define the matching rules with you, keep a durable cross-system key, and make sync conflicts visible rather than letting the last writer quietly win.
Custom middleware
When two systems can't be made to fit, we write the layer between them: translation, buffering, business rules, permissions and an audit trail. Middleware we build is documented and owned by you, not a black box you rent.
Automation triggers
Conditions evaluated against connected data — an estimate aging past a threshold, a missed call from an existing customer, a spend anomaly — firing tasks, alerts, messages or AI agent runs with the business context already attached.
Read one side, write the other.
Integration is rarely one-directional. Below: the pattern we typically use per system class, and what flows each way.
| System class | Mechanism | Typically read | Typically written |
|---|---|---|---|
| Field service (ServiceTitan) | REST + webhook | Jobs, bookings, estimates, invoices, technicians | Notes, tags, tasks, custom fields |
| CRM | REST + webhook | Contacts, lifecycle stage, activity history | Lead scores, summaries, follow-up tasks |
| Voice / telephony | Webhook + media fetch | Call events, recordings, metadata | Dispositions, transcripts, evaluations |
| Google platforms | REST (OAuth) | Campaigns, spend, leads, profile activity | Offline conversions, labels |
| Meta | REST (OAuth) | Campaigns, spend, lead forms | Conversion events, audiences |
| Web & forms | POST + server events | Submissions, sessions, source data | Routing, enrichment, confirmations |
| Databases | SQL / CDC / replica | Transactions, records, history | Derived tables, status flags |
| Legacy / no API | Batch, SFTP, scraping-of-last-resort | Exports, flat files, reports | Import files, reconciliation output |
Illustrative patterns. Actual scopes depend on platform permissions, contractual terms and the access your organization grants.
Customer intelligence → · Custom dashboards → · Custom software development →
Integrations don't fail loudly. They fail quietly.
A broken connector rarely throws an error someone notices. It just stops returning rows, and three weeks later a manager asks why the numbers look low. We build for that failure mode specifically.
- Idempotency keys so a retried request never double-writes a record.
- Exponential backoff and rate-limit budgets per platform.
- Dead-letter queues that hold failed events for inspection and replay.
- Schema-drift alerts when a source system changes shape without warning.
- Reconciliation jobs that compare record counts across systems on a schedule.
- Per-connector health visible to us and to you — not buried in a log file.
Access follows least privilege: scoped credentials, encrypted secrets, documented write permissions, and revocation you control. The same rigor we applied to payment infrastructure built around PCI and NACHA requirements applies here.
Tell us which systems refuse to talk.
We'll map the connection, name the constraints honestly — including where a platform's API simply won't allow what you want — and tell you what's actually buildable.
AI is easy to access. Making it useful is hard.
Bluefrog makes AI useful by integrating it with the way your business actually works — your software, your calls, your customers, your marketing and your revenue.
Technology development since 1997 · AI integration platforms since 2001