One Version of the Truth
Stock, orders, invoices, and customers agree across ERP, CRM, and finance - reporting stops being an argument about whose number is right.
One data layer across every system.
We design and build the middleware layer between your ERP, CRM, e-commerce, finance, and field-data platforms: API contracts, queues, and monitored pipelines that keep every record in agreement, automatically.
- API-first integration architecture with versioned, documented contracts
- Connectors, message queues, and transformations built for your exact stack
- Retry, replay, reconciliation, and monitoring on every data flow
ERP ↔ CRM ↔ Finance
Synced · Reconciled
Pipelines monitored
Retry · Replay · Alert
6
Integration domains covered
3
Structured delivery phases
2-way
Sync designed by default
Full
Post go-live operations
Integration coverage
Every layer between your systems, engineered
Middleware is not one tool - it is contracts, transport, transformation, and operations working together. We build and run all of it.
APIs & Contracts
REST & GraphQL APIsOpenAPI ContractsWebhooksAPI GatewaysAuth & Rate LimitingVersioning
Messaging & Queues
Message QueuesPub/Sub EventsDead-Letter HandlingRetry & ReplayIdempotencyOrdering Guarantees
Data Sync
Bi-Directional SyncChange Data CaptureField MappingDeduplicationConflict ResolutionBackfills
Connectors
ERP & OdooSalesforce & CRMKoboToolbox & Field DataActivityInfo & M&EE-Commerce & StorefrontsFinance & InvoicingLegacy Databases
Transformation
Schema MappingValidation RulesEnrichmentNormalizationFile & EDI FormatsCurrency & Units
Operations
Monitoring & AlertingStructured LoggingAudit TrailsSLA DashboardsError TriageRunbooks
AI-Enabled Middleware
LLM Classification & RoutingDocument & Email ExtractionEntity Matching & DedupAnomaly DetectionEvaluation SuitesHuman-in-the-Loop Review
Delivery roadmap
How a middleware program unfolds
Three structured phases with defined outputs at each gate - so you always know where you stand and what comes next.
- 1
Discovery
System landscape and contract design
Map every system that holds operational data, who owns each record, and where data disagrees today. Define the API contracts, sync direction, and failure policy for each flow.
↳ Integration blueprint - 2
Build
Connectors, pipelines, and transformations
Develop the connectors, queues, and transformation logic against sandboxed systems, with contract tests, idempotent handlers, and staged data validation before anything touches production.
↳ Validated pipelines - 3
Operate
Cutover, monitoring, and managed operations
Cut over flow by flow with reconciliation reports at each step, then run the layer with monitoring, alerting, dead-letter triage, and SLAs - as a managed service or handed to your team.
↳ Governed integration layer
Assurance Controls
Safeguards for pipelines that carry live business data.
Every delivery includes documented control gates - for audit evidence, tender compliance, and internal sign-off before anything reaches production.
- Contract-first design with versioned, documented schemas for every flow
- Idempotent, replayable message handling - no double-posting, no silent data loss
- Reconciliation reports between source and target systems you can sign off against
- Least-privilege credentials per connector with secret rotation
- Monitoring and alerting with dead-letter queues and documented triage runbooks
Expected Outcomes
What a successful middleware program delivers.
Data agreement, removed manual work, and failure handling that hold up long after the deployment closes.
No Swivel-Chair Work
Nobody re-keys data between systems. What happens in one system shows up in the others, mapped and validated on the way through.
Failures That Surface
When a system is down or a record is malformed, the pipeline retries, queues, and alerts - instead of dropping data and letting you find out at month-end.
Integration landscape
Where the middleware layer sits
Your systems keep doing what they do best. The middleware layer between them owns the contracts, movement, transformation, and monitoring of every shared record.
Your systems
ERP and inventory
Salesforce and CRM
Field data (KoboToolbox, ActivityInfo)
E-commerce and website
Finance and invoicing
Legacy systems and files
Middleware layer
API gateway and contracts- versioned schemas, auth, rate limits
Queues and event bus- ordering, idempotency, back-pressure
Transformation and mapping- validation, enrichment, normalization
AI classification and extraction- eval-gated, human review below threshold
Retry, replay, and dead-letter- failures surface, nothing drops
Monitoring and audit- alerting, SLA dashboards, trails
What you get
One customer record
Reconciled finance data
Live stock and orders
Reports that agree
Audit-ready trails
AI-enabled middleware
AI where rules run out
Deterministic pipelines move the data. AI steps handle the parts that used to need a person - reading, classifying, matching, and judging - inside the same governed layer, with the same retry, audit, and review controls as every other flow.
Intelligent Classification & Routing
Incoming emails, orders, tickets, and documents are classified by an LLM and routed to the right system, queue, or person - instead of a shared inbox someone triages by hand.
Document & Email Extraction
Invoices, purchase orders, delivery notes, and RFQs arrive as PDFs and free text. AI extraction turns them into structured, validated records posted straight into ERP.
Entity Matching & Deduplication
When systems share no common keys, AI matching links the same customer, product, or supplier across ERP, CRM, and spreadsheets - with confidence scores, not guesses.
Anomaly Detection Before Posting
Records that look wrong - a price 100× off, a duplicate invoice, an impossible quantity - are flagged and held for review before they contaminate downstream systems.
Smart Transformation
Free-text fields become normalized data: addresses standardized, units converted, categories assigned - the mappings rule-based logic can never fully cover.
Workflow Streamlining
Multi-step processes that used to need a person in the middle - check, summarize, draft, forward - run end-to-end with AI handling the judgment calls under defined thresholds.
Evaluations, not vibes
Every AI step ships with an evaluation suite.
No model, prompt, or provider change reaches production until it scores against your real historical payloads. Corrections made in review feed back into the suite, so the pipeline gets measurably better the longer it runs.
- 1
Benchmark
Eval suite built from real historical records, scored before go-live
- 2
Gate
Confidence thresholds decide what posts automatically and what waits for a person
- 3
Review
Human corrections captured in-flow, never lost in email threads
- 4
Improve
Corrections become new eval cases and training data for the next iteration
Middleware Engineering
Built like software, run like infrastructure.
Integration work fails when it is treated as glue code. We engineer the layer with contracts, tests, and observability - then operate it under an SLA, so it stays reliable as every connected system evolves.
- Versioned contracts and automated contract tests on every flow
- Idempotent handlers with retry, replay, and dead-letter queues
- Structured logging, alerting, and reconciliation reports in production
Custom Connectors
Purpose-built connectors for the systems off-the-shelf tools don't cover - legacy databases, government portals, industry platforms, and in-house software.
Event-Driven Architecture
Queues and pub/sub event flows so systems react to changes as they happen, with ordering, idempotency, and back-pressure handled by design.
ETL & Batch Pipelines
Scheduled extract-transform-load jobs for reporting, backfills, and migrations - with checkpoints and resumability instead of all-or-nothing runs.
Legacy System Bridges
File drops, EDI, database polling, and screen-level integration when the old system has no API - wrapped behind a clean contract so the rest of the stack never knows.
Contract & Integration Testing
Automated tests that pin every contract and replay real payloads, so upgrades to any connected system can't silently break the flow.
Managed Operations & SLAs
We run the layer after go-live - monitoring, alert response, dead-letter triage, and change management - under a defined SLA.
Related services
Middleware is the backbone the rest of the stack stands on.
These service areas build on a clean integration layer - the ERP it feeds, the AI it enables, and the custom software it connects.
ERPERP Implementation and DevelopmentThe system of record middleware feeds - finance, inventory, and operations on one governed platform.AI servicesAI agents on top of connected dataAgents are only as good as the data they reach. A clean integration layer is what makes production AI possible.Custom softwareCustom applications and APIsPurpose-built applications, portals, and secure APIs that plug into the same integration backbone.
Related insights
Further reading for operations and systems decision-makers.
Use these resources to understand how Leeway connects implementation control with practical AI and measurable operations.
InsightAI in ERP and CRMA practical starting model for AI initiatives inside CRM, ERP, and operational programs.Case studiesImplementation outcomesHow Leeway delivers systems programs with governance, migration control, and measurable adoption.GuideAI adoption resourcesFree guides for operators planning practical AI workflows around existing systems.