Applied LLM and agent systems
Retrieval pipelines, tool-use agents, and human-in-the-loop workflows on Claude Opus 4.8, GPT-5.5, Gemini 3.1 Pro, or open models you self-host.
Primary research for the answer-engine era, our most-cited piece.
Five constraint numbers locked before build. Six stages from discovery to hand-off.
Our enterprise AI development services start where most enterprise AI stalls, one step short of production. The demo works, then it never touches the ledger the business runs on. We build the other way around, from your security posture and your write path, and ship a system your platform team can run after we leave.
The pilot is the easy 20%. The hard 80% is everything between a working demo and a model the business trusts to write to its ledger: identity, data residency, the rollback path, the human-in-the-loop gate, and the eval suite that catches a regression before a customer does. Our enterprise AI development services are built for that 80% from the first commit, which is the only kind of work we take on.
According to S&P Global Market Intelligence, the average organization scrapped 46% of its AI proof-of-concepts before they reached production in 2025, and the share of companies abandoning most AI initiatives jumped to 42%, up from 17% the year before.
No write path. The model reads context but is never trusted to act on the system of record, so it stays a sidecar no one depends on.
No identity story. Without SSO and role-based access wired in from day one, security review stops the rollout cold.
No eval gate. Quality is judged by vibes in a demo, so the first silent regression in production erodes trust for good.
No owner after handoff. The pilot lived in a notebook on one laptop, and no platform team could run it.
Each engagement is led by one senior engineer who owns the system from data contract to deployed write path. We deliver the model and the machinery around it, built to be operated by your team after handoff.
Retrieval pipelines, tool-use agents, and human-in-the-loop workflows on Claude Opus 4.8, GPT-5.5, Gemini 3.1 Pro, or open models you self-host.
The document, vector, and structured-data layer that grounds answers in your sources, with lineage your auditors can follow.
A three-layer eval suite (reference, adversarial, regression) wired into CI, plus prompt-injection and PII-extraction tests against synthetic fixtures.
Model and prompt versioning, drift and cost monitoring, and a rollback path a release engineer can trigger in seconds.
The connectors, idempotency, and audit trail that let AI write safely to your ERP, CRM, or ledger.
The documented runbook, the eval dashboard, and the pairing sessions that leave your team able to own it.
We engineer to recognized control frameworks rather than waving a badge at them. Each item below is something we build to and document for your audit, not a certification we claim on your behalf.
Access logging, change management, and evidence collection your SOC 2 audit will sample, designed to your auditor's scope.
Documented data classification, key management, and access governance that map to your ISMS.
We classify each system and engineer its tier's obligations. High-risk Annex III deadlines were deferred to December 2027 and embedded-product obligations to August 2028 under the 2026 Digital Omnibus, so we build to the controls without front-loading a date not yet in force.
Data stays in the region you specify, processing pinned to your tenant, and no training on your data unless you direct it in writing.
Every model decision is traceable to its inputs, prompt version, and data source, so an audit trail exists before anyone asks.
We engineer to the availability and recovery objectives in your contract and instrument the system to prove them, building to your SLA rather than printing a percentage on a banner.
Clutch 4.9 of 5 · AWS, Google, and Microsoft Partner.
Where the system runs is a security decision. In every option your data and model traffic stay where your policy requires, and you hold the keys.
We deploy into your AWS, Azure, or GCP account, behind your network controls and your IAM, so the system lives where your production workloads already run.
A dedicated single-tenant environment we stand up and operate to your policy, with isolation, logging, and key management you can inspect.
For regulated or sovereign workloads, the entire stack runs on self-hosted open models inside your data center, with no outbound calls to a third-party API.
Identity is not a phase-two feature on an enterprise system. The model inherits the same permissions your people have, so it can never read or write something the requesting user could not.
SSO through your identity provider. SAML or OIDC against Okta, Entra ID, Ping, or Google Workspace, with SCIM so access follows your joiner-mover-leaver process.
Role-based access control. Permissions defined per role and enforced at the data layer, so retrieval and tool-use respect the boundaries your application already does.
Least-privilege by default. Service accounts are scoped to exactly what a task needs, and elevated actions route through an approval step.
Full attribution. Every prompt, retrieval, and write is tied to an authenticated identity and timestamp, so the answer to "who did this" is one query away.
We agree the workflow, the success metric, the data sources, and the security boundary in writing, then stand up the environment.
We build the retrieval layer, the agent or model logic, and the eval harness, grounding every answer in your sources with lineage intact.
We wire in SSO and RBAC, add the adversarial and regression eval gates, instrument observability, and run the system against real load.
We deploy to production behind your controls, hand over the runbook and eval dashboard, and pair with your team so they can operate it.

Procurement and security need a path they can approve, so you commit incrementally and see a real system before the largest spend. Each stage has a defined exit, and you own everything produced in it.
A working session to map the highest-value workflow, the data boundary, and the security requirements, ending in a written statement of work and architecture.
A fixed-scope, paid engagement that delivers one workflow as a real, evaluated, access-controlled system. You judge us on shipped software.
We harden, integrate to the system of record, and deploy inside your perimeter on the 90-day cadence, with SSO, RBAC, and eval gates in place.
We hand off the runbook and dashboards, support your team through ownership, and widen to the next workflow on a cadence you set.
Pricing follows a global delivery model with rates that run typically about 70% below comparable onshore rates, with the same named senior ownership throughout.
Founded 2017. The track record and the in-house senior ownership are what get our work past enterprise security review and into the system of record.
The questions a security team, a procurement lead, and an engineering VP each bring to the first call.
Enterprise AI development services are the end-to-end engineering of AI systems that meet enterprise requirements for security, identity, data residency, and integration with the system of record. They go beyond a model or a prototype to include the retrieval layer, the eval and guardrail harness, SSO and role-based access, observability, and the deployment topology your security team will approve. At Resourcifi the work is led by a named senior engineer from our in-house team and is built to be operated by your platform team after handoff.
We engineer for production from the first commit instead of treating it as a later phase. That means a defined write path to the system of record, SSO and RBAC wired in early, a three-layer eval gate in CI, observability with a fast rollback, and a documented runbook. We run it on a 90-day cadence that takes one high-value workflow from a signed data contract to a deployed, evaluated, access-controlled system.
We build and document to SOC 2 Trust Services Criteria and the ISO 27001 Annex A control set, scoped to your auditor and your information security management system. We do not claim a certification on your behalf, because the certification belongs to your environment and your audit. What we deliver is a system engineered to those controls, with the access logging, change management, data classification, and evidence collection your audit will sample.
You choose from three topologies. We deploy into your own VPC on AWS, Azure, or GCP behind your IAM and network controls; or we stand up and operate a dedicated single-tenant environment to your policy; or we run the entire stack fully on-prem and air-gapped on self-hosted open models with no outbound API calls. In every option your data and model traffic stay where your policy requires and you hold the keys.
We design to the Act's risk-tier model and classify each system you build with us into the correct tier, then engineer the obligations that tier carries. The high-risk obligations for stand-alone Annex III systems were deferred to December 2027, and embedded-product obligations to August 2028, under the 2026 Digital Omnibus agreement, so we build to the controls without front-loading a deadline that is not yet in force. The classification and the control mapping are documented so your compliance team can pick them up directly.
Single sign-on and role-based access control are built in from day one. We integrate SAML or OIDC against your identity provider, such as Okta, Entra ID, Ping, or Google Workspace, with SCIM so access follows your joiner-mover-leaver process. The model inherits the requesting user's permissions and is enforced at the data layer, so it can never read or write something that user could not, and every prompt, retrieval, and write is attributed to a real identity in your logs.
We run a scoped, paid pilot rather than a free trial, because the pilot produces a real, evaluated, access-controlled system you keep, not a throwaway proof of concept. Pricing follows a global delivery model with rates that run typically about 70% below comparable onshore rates, with the same named senior ownership throughout. The first scoping workshop produces a written statement of work so the cost and the exit of each stage are clear before you commit to the next.
Resourcifi was founded in 2017 and holds Clutch 4.9 of 5, with 600+ projects delivered and 95% repeat clients, all of which holds up to procurement diligence. Every engagement is led by a named senior engineer from our 200+ in-house experts, not a subcontracted bench, and our delivery runs on a documented, repeatable quality system with AWS, Google, and Microsoft partner standing. The track record and the in-house senior ownership are what get our work past enterprise security review and into the system of record.
Enterprise programs rarely stop at one system. The same in-house team and governance run your wider engineering, staffing, and marketing work.
Engineers, marketers, and back-office specialists embedded in your teams on monthly terms, with a named senior lead.
Staff augmentation →Web, mobile, and custom platform builds that integrate with the systems of record your AI writes to.
Custom software →Agents, RAG, custom LLMs, MLOps, and the rest of our Production-First AI services.
AI development company →Bring us the workflow stuck in pilot, or the one your security review keeps sending back. We will scope it, run a paid pilot that produces a real evaluated system, and deploy it inside your perimeter on a 90-day cadence.
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