LLM Integration Company in Chicago

The same LLM project prices very differently for a carrier and for a trading firm, and the difference is retention and segregation: a scoped LLM integration (a Confluence or SharePoint copilot, a supplier contract extractor, a single underwriting assistant) over eight to fourteen weeks, covering data audit, retrieval build, prompt engineering, BIPA review, evaluation harness, and production deployment, multi-system agentic work across Guidewire / Duck Creek / SAP / Salesforce, or a trading-adjacent build for DRW, Citadel, Jump Trading, GTS, or Optiver Chicago with MNPI segregation, kdb+ integration, and SEC Rule 17a-4 retention. Codazz bills fixed fees so a Chicago controller can lock the number before sending it to finance review.

BIPA prohibits collecting, storing, or transmitting biometric identifiers (face, fingerprint, voice, iris, hand geometry) without written informed consent, a written retention and destruction schedule, and a disclosed data sharing policy. Damages are $1,000 per negligent and $5,000 per intentional or reckless violation, and the Illinois Supreme Court confirmed in Cothron v. White Castle that each scan can be a separate violation. We treat any LLM workflow that touches voice transcripts, face images, drive-thru audio, signature dynamics, or video interview features as BIPA-in-scope by default, and produce a written consent flow, retention schedule, and destruction proof your general counsel can defend in a Cook County circuit court. Class certification is the existential threat in Chicago; we engineer to avoid the predicate facts.

Yes. Allstate, State Farm, Discover Financial, and Hartford operations in Chicago run Guidewire ClaimCenter / PolicyCenter / BillingCenter and Duck Creek under NAIC Model Bulletin 9999 governance. Our integrations use the Guidewire Cloud APIs and Duck Creek OnDemand REST endpoints to surface LLM-generated draft notes, adjuster decision support, and underwriting summaries inside the agent UI without bypassing the existing entitlement model. Every model contribution to an adverse action goes through a challenger evaluation tuned for the Illinois Department of Insurance unfair discrimination tests, with ECOA / Reg B adverse action language drafted by the model and reviewed by a licensed adjuster before the policyholder ever sees it. The audit log captures every prompt, retrieval, and completion for the regulator file.

For CME Group, Cboe Global Markets, DRW Holdings, Citadel, Jump Trading, GTS, and Optiver Chicago, MNPI segregation is enforced at three layers: retrieval policy that limits each user's accessible corpus to the desks and books their existing entitlement covers, prompt-time filtering that strips inadvertently included MNPI from any cross-desk query, and output-side review that scores every completion against a labelled MNPI detector before it leaves the system. Logs are written to a WORM bucket sized for SEC Rule 17a-4 retention (six years immediate, three years easy access) and synced into the existing compliance archive. We integrate with the firm's existing surveillance stack (Nasdaq SMARTS, Eventus, Behavox) rather than building a parallel one.

Yes, when the workload demands it. McDonald's, Walgreens, Caterpillar, AbbVie, Baxter, and Mondelez often have proprietary supplier corpora, technical manuals, or regulatory dossiers where a fine-tuned 8B or 70B Llama 3 or a Mixtral 8x7B beats a hosted frontier model on cost and tail-recall. We train on AWS us-east-2 GPU instances (G6e or P5) inside the client VPC, keep weights in the client S3 bucket, and document hyperparameters, training data lineage, and evaluation results under the NIST AI Risk Management Framework. For trading clients at DRW or Jump where licensing terms preclude hosted models for certain data, self-hosted Llama or Mistral is the default. Where RAG on Claude or GPT-4 wins on cost and accuracy, we say so and route accordingly.

The Artificial Intelligence Video Interview Act requires Illinois employers to disclose AI use in video interviews, explain how it works in advance, obtain candidate consent, limit who sees the recordings, and destroy them within thirty days of a candidate request. We do not ship HR LLM use cases for Chicago clients without a written consent flow, a destruction proof, a demographic data report covering race and ethnicity if the employer relies solely on AI in deciding who advances (an amendment added that obligation), and a documented bias evaluation. The same plaintiffs' bar that drives BIPA cases is moving into AI Video Interview Act suits; we engineer for plaintiff-bar discovery, not for the EEOC alone.

We build a labelled golden set from real client data (300 to 2,000 examples reviewed by Allstate adjusters, DRW quants, McDonald's franchise support leads, or Walgreens pharmacists depending on the use case), then run Ragas, TruLens, or DeepEval against every model and prompt change in CI. Faithfulness, context precision, answer relevance, hallucination rate, and where applicable fair-lending disparate-impact metrics are tracked over time; regressions fail the build. For insurance work at Allstate, State Farm, or Discover we add an NAIC Model Bulletin 9999-aligned challenger evaluation. For trading clients at CME, Cboe, Citadel, or Jump we add MNPI leakage probes. The harness is yours to keep and extend after we leave.

Default deployment is AWS us-east-2 (Columbus, Ohio), with us-east-1 (Virginia) for redundancy. Both are continental US regions that satisfy CME Group, Cboe, the Illinois Department of Insurance, and the Illinois Attorney General's documented expectations for state-resident data. For Walgreens or AbbVie workloads under HIPAA we deploy through Bedrock under BAA. For trading clients that need ultra-low latency to the CME Aurora data centre or the Cboe Equinix CH4 facility, we co-locate inference in Equinix CH1 / CH2 Chicago or run on-prem GPU clusters wired into the existing trading floor stack. Cross-border is acceptable only after a Privacy Impact Assessment signs off, typically for non-sensitive internal tooling at Mondelez, ADM, or Exelon global operations.