Transform Your Business With Enterprise AI Integration Services
Integrate AI seamlessly into your existing technology stack to streamline workflows, improve efficiency, and drive measurable business growth.
Embed AI into CRM, ERP, identity, and custom platforms — with contracts, logging, and fallback
A model that cannot authenticate as a named principal, write back through your APIs, or fail closed is a demonstration. Suraket integrates AI into CRM, ERP, service desks, identity, and custom platforms — with data contracts, logging, and a fallback when the output is not good enough to send.
Generative AI Integration is the GenAI-specific plumbing: retrieval over knowledge, prompts, write-back of drafts. This page is broader. Scores, agents, automation, vision events, and language systems all have to join the estate. Different H1, different buyer. If the project is a notebook that cannot pass identity, you are in the right place even when the model is not generative Keep the H1s distinct so a CRM score project is not sold as retrieval, and a knowledge assistant is not sold as a generic estate join.
Integration is where AI programmes stall. The model works on an extract. The CRM owner will not grant a write. The directory team will not mint a service identity. Change advisory has never seen a prompt in a release. Suraket treats those as the work, not as blockers around the “real” science. Contracts, retries, idempotency, and degraded modes are the product We treat identity, change advisory, and fallback as the product, not as paperwork around a notebook that already “works.”.
Benefits of AI Integration Services With Suraket
Accelerate Time-to-Value
Use proven frameworks, accelerators, and experienced teams to move AI solutions from concept to production faster.
Integrate Existing Systems
Embed AI into applications, data platforms, and workflows while minimizing disruption to core business operations.
Reduce Operational Risk
Deploy AI with built-in governance, security controls, monitoring, and safeguards to support reliable operations.
Connect Disconnected Data
Unify data across systems and sources to give AI the context needed for accurate insights and decisions.
Modernize Business Processes
Automate inefficient workflows to improve speed, reduce errors, increase productivity, and support scalable growth.
Where we join AI to the estate
CRM embedding
Scores, next-best-action, draft replies, and case summaries inside the CRM the team already lives in. Write-back to the object model with validation and an undo or override. We respect sharing rules. A parallel “AI CRM” is not the default.
ERP and systems of record
Read and write paths into finance, supply, HR, or industry ERPs — with timeouts, idempotency, and change advisory. Posting a hallucination to a ledger is a process incident. Dual-run and makerchecker stay where the blast radius demands them.
Identity and access integration
SSO, service principals, scoped tokens, just-in-time elevation for tools. Agents get least-privilege tool schemas, not a copied admin cookie. Directory groups remain the source of truth for who may invoke which capability.
Service desk and ITSM
Triage, draft resolution, knowledge retrieval, and ticket updates in the desk you already operate. Escalation rules stay yours. We will not let an agent close incidents it cannot evidence. Audit on every write.
Custom platform APIs
Internal HTTP and event contracts for applications you built. Versioning, compatibility windows, and consumer tests. AI is a client of your platform, not a second platform that forks the object model.
Data-plane contracts
Feature payloads, document references, image handles, and streaming events with schemas. We align with the warehouse or lake you have. Shadow CSVs in a bucket are a temporary slice, not the integration.
Middleware, queues, and events
Rate limits, retries, dead-letter, exactly-once where the record requires it. Partial failure designed. An inference timeout must not double-charge or double-case. Circuit breakers protect the system of record from a model storm.
Agent tool-calling into the estate
Permissioned tools with schemas, timeouts, and human-on-the-loop on high-impact actions. Prompt injection assumed. Tool output is logged. If the job only needed a score on a form, we will not invent an agent to look modern.
Vision and event ingress
Holds, counts, and alerts from vision systems into WMS, MES, or case files. See Computer Vision Solutions for the pipeline; this service is the join: signals, acknowledgements, degraded mode when cameras fail.
Batch and dual-run paths
Nightly scores, champion–challenger, and comparison against the current process before a live write. Finance and risk often need this before an online path. We treat batch as a first-class integration, not as “lesser real-time.”
Observability and cost join
Traces, metrics, and token or GPU spend in the same operations view as the host application. Budget alarms. An unbounded chat loop is a finance incident. We wire the meters before go-live, not after the first bill shock.
Runbooks and fallback drills
What operators do when the model is wrong or gone. Feature flags to disable a write path without taking the host application down. Tabletop the failure with the team who will be paged. Integration is not done until that drill exists.
Outcomes we’ve delivered
How we integrate without leaving a sidecar
We map the workflow and the systems of record first, then the allowed tools and data, then the integration layer with rollback. A
pilot uses a real team on a real week. Harden means load, errors, and who is paged. Dates follow access. We will not promise golive before identity and contracts are visible to the platform owners who must live with them.
01
Map workflow and systems of record
- Name the step where a score, draft, or action appears, and the step where a human still decides. Write it into the brief before the next phase starts.
- Inventory CRM, ERP, identity, custom APIs, and batch jobs on the path. Include change windows. Treat it as a gate, not as a preference we can revisit later.
- Capture current failure modes: timeouts, duplicate posts, poisoned reference data. Operations must be able to run this without a hallway explanation.
- Agree anti-goals: privileged bypass, silent writes, a second UI nobody will open. Security sees it before connectors or weights move.
02
Define contracts and permission
- Specify schemas, idempotency keys, and error codes. Version from day one. If it cannot be named, we do not pretend the phase is done.
- Design identity: user context versus service identity, and where each is allowed. Record the owner so the next meeting does not relitigate it.
- List tools an agent may call. Least privilege. Human-on-the-loop on high-impact verbs. Keep the blast radius visible in the same sentence as the task.
- Set evaluation tasks on the integrated flow, including permission-denied cases. Leave an artefact someone else could execute without us in the room.
03
Build the join with rollback
- Implement adapters, queues, and flags so the host application can disable AI without a deploy panic. Dual-run or draft-lane until the error budget is evidenced.
- Put tracing and audit fields on every call. Cost meters on inference. Change advisory treats this as part of the same release as the code.
- Handle partial failure: compensating actions or explicit operator queue. Identity and grants are assumed here, not hoped for later Put the owner and the artefact in the same brief.
- Contract tests in CI. A model change that breaks a field is a failed build. A missing degraded mode is a stop, not a footnote.
04
Pilot with a real team
- Named users, a defined week, a defined volume. Not a hallway demo. Evaluation tasks include the failure case, not only the happy path.
- Compare against the current process. Dual-run where writes matter. Cost and latency envelopes are design inputs, not a bill shock.
- Collect override reasons. Integration bugs and model bugs are separated in the log. The old process has an explicit end date or an explicit stay.
- Watch latency tails and rate limits. Protect the system of record. Traces on from the first slice so incidents have a starting point.
05
Harden and transfer
- Load, chaos on inference down, identity expiry, poison payloads. Least privilege is verified, not copied from a demo service account.
- On-call, SLOs, and the flag that stops writes. Drill the fallback. Rollback includes policy, index, and weights — not only application code.
- Change advisory for production promotion. Model and contract versioned together. The people who own the job must be in the cohort, not only innovation.
- Handover runbooks, schemas, and dashboards to the team that pages. We would rather delay than teach the wrong lesson on fake objects.
Industries We Support
We deliver industry-focused AI integration solutions that address real operational challenges and create measurable business value.
Healthcare
- Clinical Decision Support: AI-powered systems for faster, more informed clinical decisions.
- Diagnostic Solutions: ML-powered tools for real-time disease and condition detection.
- Patient Data Integration: Secure connectivity across EHRs and healthcare systems.
- Medical Imaging AI: Computer vision for radiology, pathology, and diagnostic analysis.
Financial Services
- Identity Verification: AI-powered facial recognition for accurate identity and relationship verification.
- Document Processing: Automate identity checks, documentation, and rule-based workflows.
- Fraud Detection: Identify suspicious activity and assess financial risks in real time.
- Credit Risk Assessment: Improve risk scoring using diverse customer and financial data.
Retail
- Property Appraisal: AI-powered analysis for accurate room and restricted-item identification.
- Appraisal Management: Unified SaaS platforms for secure and scalable appraisal workflows.
- Demand Forecasting: Predict demand and optimize inventory to reduce shortages and excess stock.
- Personalized Experiences: Recommendation engines and intelligent pricing tailored to customer behavior.
Manufacturing
- Smart Inventory: AI-powered inventory management to reduce downtime caused by material shortages.
- Predictive Maintenance: Analyze equipment data to identify potential failures before they occur.
- Quality Automation: Use computer vision to detect defects and improve production quality.
- Production Optimization: AI-driven scheduling and resource planning for more efficient operations.
Education
- Content Moderation: AI-powered multilingual moderation for safer digital learning environments.
- Automated Assessment: AI-assisted grading, evaluation, and feedback for faster assessment.
- Student Analytics: Identify performance patterns early and enable targeted academic support.
- Intelligent Teaching Systems: AI-powered tools that assist educators and enhance learning experiences.
Why organisations commission this work
Identity-aware by default
The model or agent sees what the user is allowed to see. Row-level and object-level rules travel with the call. A privileged service account that bypasses the directory is treated as a defect, not a shortcut to a demo.
Contracts that version
Inputs, outputs, error codes, and schemas under change control. Silent field drift is how integrations rot. Consumers should not parse a mystery JSON that changed on a Thursday.
Fallback and fail-closed
When inference is slow, down, or below threshold, the workflow still has a path: queue, default, human. Fail-open on a credit, clinical, or payment write is not an integration pattern we will ship.
Logging you can audit
Who called, what was retrieved or scored, what was written, latency, cost. Traces join application APM where you already page. “The model said so” is not an evidence trail.
Evaluation in the path
Offline sets and online monitors on the integrated flow, not only on a lab extract. Integration without measurement is hope. Promotion of a new model includes the contract tests.
Operations like any other service
SLOs, on-call, rate limits, cost envelopes. AI is not exempt from capacity planning because it is new. We will not leave you with a sidecar nobody runs.
Trusted by major businesses
Integrate AI Into Your Enterprise
Embed AI into your existing systems and workflows to improve efficiency, reduce costs, and accelerate innovation. Our AI integration services are designed to deliver measurable business value within 90 days.
FAQs About AI Integration Services
Can AI sit on legacy platforms?
Yes, with APIs, files, queues, and middleware. We treat this as modernization of the join, not as a new island. Some estates need an anti-corruption layer so a model never sees a poisonous schema. That layer is in scope. We will not pretend a thirty-year-old core will grow a native inference API this quarter. We will also not use legacy as an excuse to dump CSV extracts forever — the contract should still version.
How is this different from Generative AI Integration?
Generative AI Integration is retrieval, prompts, knowledge permissions, and write-back of generated artefacts. This page is the broader join: predictive scores, agents, automation, vision events, and any model that must authenticate and fail closed. A programme can need both. The H1s stay different so a CRM score project is not sold as a RAG programme, and a knowledge assistant is not sold as a generic ESB story. A programme can need both pages. The H1s stay different so procurement is not buying a blob called AI integration that hides the actual join.
Do you build the model as well?
Often the model already exists in a lab, a vendor, or a Custom AI workstream. Integration is then the centre. We can bring Custom AI or Development in the same programme when the model is not production-shaped. We will not hide a modelling science project inside an integration SOW. If evals fail on production-like data, we stop the join until the model is honest. We will not hide a modelling science project inside an integration SOW; if evals fail on production-like data, the join waits until the model is honest.
How long does an integration take?
It follows access, the number of systems on the path, and change-advisory calendars. We do not date go-live before identity and a contract are visible. A single CRM write of a draft can be a short slice; an ERP posting path with dual-run is longer. Anyone quoting a fixed number of weeks from a homepage has not seen your directory. We estimate after the map. A single CRM write of a draft can be a short slice; an ERP posting path with dual-run is longer, and we will not pretend otherwise from a homepage.
What about agents that call many tools?
Tool-calling is in scope here as permissioned integration. Multi-step planning and the agent control model also live on Custom AI and the Generative & Agentic hub. Integration still owns the contracts, identity, and kill switches. An agent without a tool schema and an audit log is not integrated — it is a script with credentials. We will not ship that. Multi-step planning also lives on Custom AI and the hub; integration still owns contracts, identity, and kill switches, or the agent is not integrated. If the work is stuck at “it works in the notebook,” start here. Suraket will wire the model to CRM, ERP, identity, and the platforms you already run — with contracts, logging, fallback, and an operations path someone will actually page.
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